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P-1504 The Applied AI team at Databricks sits at the forefront of advancing GenAI-powered products. Over the past years, we’ve launched Databricks Assistant , AI/BI Genie , and Agent Bricks working with product teams, and made significant strides in LLM quality for these products. These products are used by 100s of thousands of Databricks users every day. We are tackling challenging problems like code suggestion, error detection and correction, text-to-sql generation, automatic pipeline generation, knowledge QA and many others. As our GenAI products continue to evolve, we are seeking multiple GenAI Engineers from junior levels to more senior levels to drive the next phase of development. In 2025, we will focus on enhancing LLM quality, expanding GenAI capabilities across Databricks products, and strengthening our platform architecture to enable seamless AI interactions at scale. Key Responsibilities Shape the direction of our applied AI areas and intelligence features in our products . Drive the development and deployment of state-of-the-art AI models and systems that directly impact the capabilities and performance of Databricks' products and services (e.g., Databricks Assistant and AI/BI Genie). Develop novel data collection, fine-tuning, and LLM technologies that achieve optimal performance on specific tasks and domains. Design and implement ML pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation, enabling rapid experimentation and iteration. Work closely with cross-functional teams, including AI researchers, ML engineers, and product teams, to deliver impactful AI solutions that enhance user productivity and satisfaction. Build scalable, reusable backend systems to support GenAI products across the company. Develop robust logging, telemetry, and evaluation harnesses to ensure reliable model performance. What We’re Looking For 2-8 years of machine learning engineering experience in high-velocity, high-growth companies. Alternatively, a strong background in relevant ML research in academia will be considered as an equivalent qualification. Strong track record of working with language modeling technologies. This could include the following: Developing generative and embedding techniques, modern model architectures, fine tuning / pre-training datasets, and evaluation benchmarks. Proficiency in Python, TensorFlow/PyTorch, and scalable ML architectures. Ability to drive end-to-end model development, from research and prototyping to deployment and monitoring. Strong analytical and problem-solving skills, with a passion for improving AI-driven user experiences. Strong coding and software engineering skills, and familiarity with software engineering principles around testing, code reviews and deployment. Experience with LLM fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) is a bonus. Why Join Us? At Databricks, we are building state-of-the-art AI solutions that redefine how users interact with data and our products. You’ll have the opportunity to shape the future of AI-driven products at Databricks, work with cutting-edge models, and collaborate with a world-class team of AI and ML experts. If you're excited about pushing the boundaries of AI in real-world applications, we’d love to hear from you! Please note we are open to employees working from our Mountain View, CA office for this position. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . Local Pay Range $190,000 - $285,000 USD About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter , LinkedIn and Facebook . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Our Mission Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life. For more information, see our website at altoslabs.com. Our Value Our Single Altos Value: Everyone Owns Achieving Our Inspiring Mission . Diversity at Altos Altos Labs has been named one of the Top 3 Biotech Companies and ranked for the second year on the Forbes 2026 Best Startups in America list. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. We are all accountable for sustaining a diverse and inclusive environment. What You Will Contribute To Altos As part of our team, you will help to accelerate and optimize our progress in developing unified, multi-modal generative foundation models for multiscale biology. You will be an integral part of our multidisciplinary teams building the computational platforms that will enable Altos to achieve its mission. In this role, you will partner and collaborate with other multidisciplinary Scientists and Engineers across the Institute of Computation to design, build, and scale state-of-the-art foundation models that tackle biological questions and aid in the discovery of novel interventions for aging and disease. You will focus on the synthesis of unstructured multimodal signals with the structured relational data and knowledge graphs that represent biological reality. The successful candidate will thrive in a fast-paced environment that stresses teamwork, transparency, scientific excellence, originality, and integrity. Responsibilities As a Staff Machine Learning Scientist, you will use your experience to focus on designing, developing, and evaluating state-of-the-art foundation models, at scale, to benefit the research. Pre-train and fine-tune large-scale machine learning systems using multimodal biological data, natural language, and structured relational inputs. Architect and implement novel hybrid models that integrate Large Language Models (LLMs) with Graph Neural Networks (GNNs) for multi-hop reasoning over biological knowledge graphs . Develop Relational Foundation Models (RFMs) that enable zero-shot predictive tasks over heterogeneous, multi-table biological datasets. Lead the design of efficient data loading strategies and distributed training recipes (e.g., FSDP, DeepSpeed) to train models across multiple GPU nodes. Gain insights into model performance based on theory, deep research, and the mathematical underpinnings of set-invariant and graph-structured architectures . Apply strong coding experience to model development and deployment, ensuring research prototypes transition into reliable, scalable production systems. Stay up-to-date on the latest developments in deep learning—including native early-fusion and Mixture-of-Experts (MoE) architectures—and apply this knowledge to Altos' research . Mentor junior staff while maintaining a high individual technical contribution to the core research ecosystem and peer-reviewed publications. Who You Are We are looking for someone who is: Excited about the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities. Highly collaborative in mindset and ways of working across research and engineering boundaries. Self-motivated to drive and deliver on long-term technical projects and scientific goals. Demonstrates the desire to grow professionally and expand their skillset in biology, machine learning, and/or drug development. Able to communicate and explain the design, results, and impact of complex AI architectures to both scientific and non-scientific staff. Keen to contribute to seminars and scientific initiatives within Altos and the broader AI research community. Minimum Qualifications PhD in Computer Science, Machine Learning, or a similar quantitative field with 5+ years of relevant work experience in academic or industry settings. Prior experience in developing and implementing novel generative AI models, specifically in multimodal integration, GraphRAG, or relational deep learning . Deep understanding of Machine Learning principles and how they apply to diverse architectures like Transformers, GNNs, and diffusion models . Very strong programming skills in Python and deep learning libraries (e.g., PyTorch, JAX, Hugging Face Transformers/Accelerate). Proven experience with multi-GPU and distributed training at scale (e.g., DDP, FSDP, DeepSpeed, Megatron, or Ray). Strong track record of published, peer-reviewed innovative AI/ML research at top-tier conferences (NeurIPS, ICML, ICLR, CVPR). Preferred Qualifications Familiarity with tabular foundation models (e.g., TabPFN) and in-context learning strategies for structured data . Specific experience in native multimodal modeling (early-fusion) or the synthesis of LLMs and Knowledge Graphs . Track record of ML applied to biological data, such as NGS data (RNA-seq, ATAC-seq), biological imaging (microscopy, IF), or spatial transcriptomics. Experience in optimizing large-scale inference via quantization, distillation, or memory-efficient attention mechanisms. The salary range for Redwood City, CA : Scientist I, Machine Learning: $200,900 - $257,500 Scientist II, Machine Learning: $226,200 - $290,000 Senior Scientist I, Machine Learning: $257,400 - $330,000 The salary range for San Diego, CA : Scientist I, Machine Learning: $179,400 - $230,000 Scientist II, Machine Learning: $212,900 - $273,000 Senior Scientist I, Machine Learning: $239,500 - $307,000 Exact compensation may vary based on skills, experience, and location. LI-NN1 For UK applicants, before submitting your application: - Please click here to read the Altos Labs EU and UK Applicant Privacy Notice ( bit.ly/eu_uk_privacy_notice ) - This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment. Equal Opportunity Employment We value collaboration and scientific excellence. We believe that a culture of belonging are foundational to scientific innovation and inquiry. At Altos Labs, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. We are all accountable for sustaining an inclusive environment. Altos Labs provides equal employment opportunities to all employees and applicants for employment, without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Altos prohibits unlawful discrimination and harassment. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training. Thank you for your interest in Altos Labs where we strive for a culture of scientific excellence, learning, and belonging. Note: Altos Labs will not ask you to download a messaging app for an interview or outlay your own money to get started as an employee. If this sounds like your interaction with people claiming to be with Altos, it is not legitimate and has nothing to do with Altos. Learn more about a common job scam at https://www.linkedin.com/pulse/how-spot-avoid-online-job-scams-biron-clark/

The climate crisis is the defining challenge of our time—but it’s also the greatest opportunity for innovation, and a challenge we’re proud to take on. At Overstory, we’re harnessing cutting-edge technology to enable a resilient electrical grid that keeps communities thriving as our world changes. The grid is the backbone of life as we know it. It powers hospitals, keeps food fresh, and ensures communities stay connected. But extreme weather, aging infrastructure, and growing wildfire risks are putting this critical system under pressure. All of this combined makes the electric utility industry the greatest opportunity for tackling climate change. One of the leading causes of catastrophic wildfires and power outages? Trees and brush coming into contact with power lines. That’s where we help. At Overstory, we use AI and advanced satellite imagery to pinpoint and prioritize vegetation risks before they materialize. By giving utilities critical analysis on those risks, we’re helping prevent outages, reduce wildfire risks, and accelerate the transition to a safer, more resilient grid. Our team spans the Americas and Europe, and we work with utility partners across the Americas and beyond. We’re outdoor enthusiasts, musicians, artists, athletes, parents, and adventurers. What unites us is a passion for solving complex problems, a commitment to climate action, and the belief that technology should be a force for good. Join us to help us build a more resilient world together. Role & Team As a Staff Machine Learning Engineer at Overstory, you will lead the development and scaling of our Wildfire Fuel Detection Model. This core engine powers how we understand vegetation structure, fuel loads, and wildfire risk from satellite and environmental data. You’ll help shape the next generation of Overstory’s modeling capabilities by combining cutting-edge ML techniques, large-scale geospatial data, and real-world domain expertise. Reporting to our VP of Product Engineering, you’ll work closely with data scientists, ML engineers, and product teams to ensure our wildfire models are accurate, robust, and production-ready – balancing scientific rigor with practical engineering excellence. As a senior technical leader, you’ll mentor other engineers, drive architectural decisions, and define standards for modeling, experimentation, and deployment across Overstory. Time zone requirement: Eastern North America (NST, AST, EST) What You’ll Do In collaboration with data, ML, and science colleagues, you will: Architect and build advanced ML models to map and predict vegetation and fuel conditions across diverse geographies. Design and maintain robust data and feature pipelines for large-scale geospatial and temporal data. Partner with wildfire science and product teams to define modeling objectives and evaluation metrics tied to real-world impact. Build reproducible experimentation frameworks and model evaluation workflows. Scale models from research to production with a focus on performance, reliability, and explainability. Lead the evolution of ML systems, tooling, and processes — ensuring that our wildfire fuelscape models remain state-of-the-art and maintainable. Collaborate with MLOps peers to streamline training, inference, and monitoring in production environments. Skills & Experience Experience thriving at the intersection of machine learning, geospatial data, and environmental science; deeply motivated by the opportunity to reduce wildfire risk through data-driven insights 10+ years of experience designing and building production-grade ML pipelines and systems Strong background in deep learning, computer vision, or remote sensing Skilled in designing end-to-end ML systems — from data ingestion and preprocessing to deployment and monitoring Hands-on experience with frameworks like PyTorch, TensorFlow, XGBoost, or LightGBM, and data tools like Dask, Spark, or GeoPandas Familiarity with GCP and Vertex AI, or similar cloud-based ML platforms Strong communication skills and ability to collaborate across technical and scientific domains Comfortable leading architectural discussions and mentoring other engineers Nice To Have Background in wildfire science, forestry, or remote sensing Experience integrating physics-based models with ML or working with active learning and uncertainty quantification Experience in model interpretability and data provenance for environmental ML systems Experience with deep learning models for weather or climate data Experience in remote-first or globally distributed teams Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description. What We Offer Competitive, location-specific compensation and benefits Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around Home office stipend, coworking and ongoing education budgets A company culture that genuinely embodies each of our core values To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis About Our Team We are a group of 100 people from all over the world. Fifteen nationalities are represented in our team and at last count we speak fourteen languages: English, Dutch, French, Spanish, German, Italian, Portuguese, Russian, Luxembourgish, Lithuanian, Bulgarian, Cantonese, Estonian, and Danish. We work remotely from eleven countries and are looking for candidates that are living and working in one of them: United States, the Netherlands, United Kingdom, Ireland, Estonia, Portugal, France, Sweden, Switzerland, Denmark and Canada. We gather once a year in-person for our unforgettable team gathering event. We also offer the option to occasionally meet up for in-person collaboration. Diversity & Inclusion The climate crisis is a human crisis that requires diverse perspectives to solve. We place enormous value on diversity and believe that the best ideas emerge when people with different backgrounds and experience work together. We remain committed to scaling a team that reflects the communities we serve, and strive to uphold equitable and inclusive practices across every aspect of our business. We are responsible for creating and maintaining a culture where everyone - regardless of background - has a voice in building a sustainable future. Our Values Tackling the climate crisis is our greatest mission. We act with urgency. Our curiosity fuels our growth. We recognize that change is constant, and we find joy and power in exploration. We’re rooted in diversity. Just as ecosystems need biodiversity to thrive, our resiliency comes from our differences. We care for each other. We love the power of machines but we nurture each other as humans. Trust is fundamental. We assume the best in everyone, and we share ideas openly so that we have a positive impact. _________________________________ Use of AI in Our Hiring Process We sometimes use AI tools to support parts of our hiring process, such as helping us manage applications more efficiently or ensuring job descriptions are clear and inclusive. All hiring decisions are always made by people, not machines. Any data processed by AI is handled securely in line with GDPR and our Privacy Notice .

About Us Valo Health is a human-centric, AI-enabled biotechnology company working to make new drugs for patients faster. The company’s Opal Computational Platform transforms drug discovery and development through a unique combination of real-world data, AI, human translational models and predictive chemistry. Our talented team of biologists, chemists and engineers, armed with advanced AI/ML tools, work together to break down traditional R&D silos and accelerate the speed and scale of drug discovery and development. Valo is committed to hiring diverse talent, prioritizing growth and development, fostering an inclusive environment, and creating opportunities to bring together a group of different experiences, backgrounds, and voices to work together. We embrace new ways of learning, solve complex problems and welcome diverse perspectives that can help us advance patient-centric innovation. Valo is headquartered in Lexington, MA, with additional offices in New York, NY and Tel Aviv, Israel. To learn more, visit  www.valohealth.com . About the Role... As a Staff Data Scientist, Machine Learning in Epidemiology and Patient Data Products, you will be a core member on a team of data scientists building a powerful computational platform for advancing the discovery and development of new medicines. In this role, you will develop machine learning tools for patient data and drive their adoption across teams, under the guidance of epidemiology and biology program leads. Successful candidates will work with a diverse group of scientists and domain experts, in ways that cut across traditional industry boundaries in an innovative startup environment. What You’ll Do… Your primary areas of responsibility will be: As a senior member of our team, you will lead the development of machine learning (ML) methods and analyses of patient data with diverse stakeholders. For example, integrate clinical insights into supervised and unsupervised learning approaches and generate patient profiles. Perform project-specific hands-on analysis and modeling of high-dimensional longitudinal real-world data, spanning electronic medical records (EHRs), clinical notes, sequencing data, and multi-omics, using modern data science tools in cloud environments. Contribute to the design, implementation, and evaluation of innovative machine learning approaches for patient data to provide novel clinical insights. Be comfortable with scientific uncertainty and embrace curiosity and creative solutions. Many of the challenges we tackle don’t have known solutions or established pathways. Use your technical knowledge and intuition to articulate and break down large problems into solvable pieces. There are a lot of problems to solve; you’ll need to prioritize which of these are critical-path today from those that can wait. Be a dynamic and active team member, championing shared coding standards, participating in code reviews, and providing regular updates on your work and input into the work of your colleagues. What You Bring… MS, MPH, or PhD in health data science, biostatistics, or a related quantitative field, with 5 years of experience developing and applying ML methods, including at least 3 years working directly with real-world patient data. Experience in a biopharmaceutical, epidemiological or biostatistical setting is a plus. Extensive experience developing and implementing machine learning solutions in healthcare databases, including EHRs, administrative claims, and patient registries. Familiarity with U.S. and global medical coding ontologies and data models (ICD, ATC, LOINC, SNOMED, CPT, HCPCS, OMOP, etc.). Confident working with highly sparse and high-dimensional data. Experience processing and mining clinical notes is a plus. Extensive experience building, maintaining, and operationalizing ML pipelines, and translating model outputs into meaningful insights for diverse audiences. Broad proficiency across core ML paradigms (e.g., supervised, unsupervised, semi-supervised) and experience with linear and logistic regression, classification and tree‑based methods, clustering and dimensionality‑reduction techniques, and deep learning architectures. Hands-on experience with representation learning and transformer-based and other sequence models is a plus. Strong grounding in key components of the ML development lifecycle, including evaluation metrics, hyperparameter tuning, model selection, feature engineering and selection, model explainability, and MLOps best practices. Mastery of Python and modern data science tools (e.g., scikit-learn, PyTorch, statsmodels, SciPy, MLlib, MLflow). Experience with AI-assisted coding tools (e.g., Claude Code) is a plus. Comfortable working in ambiguous problem spaces; experience working in a start-up or agile work environment as part of cross-functional project teams. Ability to lead and facilitate meetings and work collaboratively on multi-disciplinary project teams. Exceptional time management, ability to prioritize multiple tasks simultaneously, and deliver products on time every time. Enthusiastic about documentation–ensuring that all analyses are clear and reproducible with thorough documentation of key assumptions and decision points. You May Also Bring… Advanced knowledge of biostatistics approaches, including inferential and predictive modeling. Experience in causal approaches for observational studies, including propensity score methods, bias adjustment, and covariate selection and adjustment. Familiarity with or exposure to traditional drug discovery and development processes and approaches. Remote Salary Range $165,000 - $190,000 USD CA Salary Range $175,000 - $220,000 USD Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Valo Health currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Valo Health's good faith estimate as of the date of publication and may be modified in the future. Please note: At this time, we are only able to consider candidates who currently have permanent US work authorization without the need for immediate or future sponsorship.

About us Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future. At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact. Make Wayve the experience that defines your career! The Role We're looking for an exceptional leader to spearhead our new Application Engineering team, a self-sufficient and high-impact group focused on localising and advancing our autonomous driving technology for the US market. This is a unique opportunity to shape Wayve’s AV capabilities in the US from the ground up. As a founding manager, you’ll lead a small but mighty team of engineers working across robotics, machine learning, and systems integration. You'll drive development of autonomy features tailored for US's road infrastructure, cultural driving behaviours, and regulatory landscape, ensuring our AV stack performs safely and effectively in this highly distinctive environment. We’re looking for someone who thrives in self-directed, startup-like conditions, capable of setting a vision, executing fast, and making robust decisions independently — while staying aligned with global engineering efforts. This role requires breadth: strong experience across AV systems, including robotics and autonomy, is essential. If you also bring deep expertise in machine learning, that's a major plus. Key Responsibilities: Build and lead a self-sufficient AV development team in the US, hiring and mentoring top talent across Robotics and ML. Deliver autonomy capabilities tailored to road conditions and driving norms, in close collaboration with central Autonomy teams. Drive full-cycle development: from identifying local autonomy needs, to designing, implementing, testing, and deploying features into production. Ensure the team upholds Wayve’s high engineering standards, while operating with agility and independence. Work closely with OEM partners in the US — representing Wayve’s autonomy team in technical discussions, capturing product requirements, and shaping joint development plans. Establish close working relationships with our product and vehicle operations teams in the US. About you To be successful in this role, you'll bring strong technical expertise, proven leadership skills, and a passion for building robust autonomous systems that can adapt to diverse real-world challenges. Essential A strong background in robotics and autonomy, with experience building and deploying systems that operate in real-world environments. Demonstrated ability to lead and grow high-performing engineering teams, ideally in geographically distributed or independent settings. Comfortable with ambiguity: you can define goals, carve out roadmaps, and deliver high-impact work with minimal supervision. Broad technical fluency: capable of reviewing and guiding work across software engineering, ML, controls, and systems integration. Excellent communication skills: you’re able to clearly convey technical context and strategic vision across cultures and time zones. Strong product sense and stakeholder management skills: you’re comfortable interfacing directly with OEM customers and representing engineering in external-facing conversations. Desirable Prior experience in autonomous vehicles or robotic systems operating at scale. Familiarity with US's road environment, driving behaviour, or AV regulatory landscape. A strong foundation in machine learning and its application to real-time decision-making or perception systems. This role is a full-time role based in Sunnyvale, CA or Detroit (hybrid) and the reasonably estimated salary for this role ranges from $336,400 to $381,600, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. We operate core working hours so you can determine the schedule that works best for you and your team. LI-KM1 Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know. We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply. At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law. For more information visit Careers at Wayve. To learn more about what drives us, visit Values at Wayve For US candidates only, please visit E-Verify Notice and Participation and Right to Work DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.

About us Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future. At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact. Make Wayve the experience that defines your career! The Role As an ML Engineer within the Application Engineering team, you’ll lead critical initiatives that push the frontier of model-based autonomous driving—both in terms of core driving performance and feature-level intelligence such as personalisation, comfort, and collaboration. You’ll design and deliver ML-driven behaviors that scale from assisted to autonomous driving. Your work will span across model architecture, data pipelines, evaluation frameworks, and real-world deployment. You’ll collaborate deeply with AI Platform, Simulation, Robot SW and Model Release teams to build systems that are performant, adaptable, and ready for production. Responsibilities: Develop and improve end-to-end driving models with state-of-the-art performance, robustness, and generalization. Lead projects on personalized and collaborative driving, including behavior conditioning, comfort tuning, and user alignment. Build evaluation pipelines and metrics for both closed-loop and open-loop driving performance and product readiness. Curate and mine real-world and synthetic data to drive scenario diversity, coverage, and feature-specific development. Influence architecture choices, training methodologies, and deployment pathways for production-scale learning systems. Collaborate cross-functionally across various teams to ensure integration and iteration velocity. Mentor senior engineers and shape the long-term technical direction across Autonomy. About you: In order to set you up for success as a Machine Learning Engineer at Wayve, we’re looking for the following skills and experience. Essential Extensive and proven track record of shipping deep learning systems to production. Expert in deep learning (esp. sequential models, control, planning, or perception). Proficient in Python and other relevant languages (e.g. C++ and CUDA) and ML frameworks (esp. PyTorch), with a solid foundation in software engineering practices. Experience with real-time systems or robotics, ideally with simulation- or vehicle-in-the-loop components. Ability to lead technical initiatives across teams, drive alignment, and mentor engineers. Desirable Prior work in autonomous driving, imitation learning, or trajectory prediction. Familiarity with personalization, human behavior modeling, or driver intent inference. Experience integrating ML systems into production hardware or multi-agent simulation. This role is a full-time role based in Sunnyvale or Detroit (hybrid) and the reasonably estimated salary for this role ranges from $283,500 to $381,600, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. We operate core working hours so you can determine the schedule that works best for you and your team. LI-KM1 Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know. We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply. At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law. For more information visit Careers at Wayve. To learn more about what drives us, visit Values at Wayve For US candidates only, please visit E-Verify Notice and Participation and Right to Work DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.