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Perplexity is looking for a Search Machine Learning Engineer Intern to help build the next generation of advanced search technologies, with a focus on retrieval and ranking. You will work closely with experienced engineers to improve search quality, experiment with new models, and ship features that directly impact how users search and discover information. Internship program: 12 - 24 weeks, full-time, in-person in the Belgrade office. Responsibilities: - Contribute to experiments that improve search quality through better models, data usage, and evaluation tools, under the guidance of senior engineers. - Design and implement components of the search platform and model stack, including retrieval, ranking, and classification models. - Train evaluating models (including LLM-based approaches) for retrieval, ranking, and classification tasks. - Support deployment and monitoring of search and ranking models in a scalable and performant way. - Help build and iterate on RAG pipelines for grounding and answer generation. - Collaborate with Data, AI, Infrastructure and Product teams to deliver improvements quickly and learn best practices in production ML. Qualifications: - Strong foundation in machine learning and statistics, with coursework or projects related to information retrieval, ranking, or recommender systems. - Experience with Python and common ML frameworks (e.g. PyTorch, TensorFlow, JAX) through academic, open source, or personal projects. - Familiarity with evaluating model quality using offline metrics and/or A/B testing is a plus, but not required. - Previous experience (internships, research, or significant projects) working on search, recommendation, or NLP is a plus, but not required. - Self-driven and curious, with a strong sense of ownership, willingness to learn, and comfort working in a fast-paced environment - Experience with Rust will be a plus

ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE ROLE LangChain Academy is how developers, engineers, and AI practitioners go from curious to capable on LangChain’s products. We’re looking for an experienced Education Engineer to own the development of curriculum that turns developers into proficient agent builders. This is a high-craft, high-ownership role at the intersection of software engineering and education. You’ll design and build the courses, tutorials, and live workshops that teach the LangChain ecosystem to a community of over 1 million developers — many of whom are building production agents for the first time. The bar is high: developers can tell the difference between content that genuinely helps them build and content that’s just a feature tour. Your job is to create content that consistently clears that bar. You’ll work closely with LangChain’s engineering team to stay at the frontier of what’s possible with LangGraph, LangChain, and the broader ecosystem, and work with the Technical Content Manager to shape curriculum strategy and prioritize what gets built. You’ll also partner with the Education Marketing Lead on course launches, YouTube content, and live events. WHAT YOU’LL DO CURRICULUM & COURSE DEVELOPMENT - Build the courses that define how developers learn to build agents. Design and develop end-to-end curriculum for LangChain Academy - from scoping and structure to hands-on labs and assessments — that take developers from zero to proficient with our products. - Partner with LangChain engineers to stay at the frontier. Work closely with the engineering team to understand what’s new, what’s changing, and what developers need to know. Translate that into curriculum. - Write code that teaches. Build the notebooks, example apps, and working code samples that sit at the core of every course. The code needs to be clean, well-structured, and genuinely instructive. - Build the conceptual foundation developers need to build well, not just build. As coding agents handle more of the implementation, what developers need most is a clear mental model of what’s possible and what good looks like — the right architecture, the right tradeoffs, the right patterns. Craft explanations, diagrams, and frameworks that develop genuine understanding. - Keep curriculum current. Agent engineering is a fast-moving field. Own the ongoing review and revision of existing courses to keep them accurate, relevant, and aligned with the latest LangChain releases and agentic applications. LIVE EDUCATION & COMMUNITY - Represent LangChain at workshops, meetups, and conferences. Design and deliver live technical education at developer events — from intimate hackathons to large conference stag

As a Technical Program Manager for the Platform team, you will partner with engineering teams to directly accelerate the development and maturity of the Scale Generative AI Platform (SGP) . We are looking for a TPM who has actively built and shipped products in the past and understands how to deliver robust, scalable developer tooling and distributed systems. In this role, you will own the strategic alignment and end-to-end execution of our most critical infrastructure initiatives—from initial scoping to measurable, company-wide and customer-ready adoption. You will serve as the core communication backbone and connective tissue between platform engineering, product teams, and executive leadership. Operating in a hyper-growth, demanding AI environment, you will translate SGP’s architectural complexities into clear execution strategies , unblock engineering bottlenecks, proactively mitigate deployment risks, and ensure our foundational platforms deliver reliable, performant, and secure systems capable of global-scale deployment. Key Responsibilities - Lifecycle & Platform Delivery: Lead strategic planning and high-velocity execution for SGP core capabilities (orchestration layers, model serving, APIs). Manage features from technical scoping and architecture design through production launch. - Cross-Functional GenAI Alignment: Drive execution and manage complex technical dependencies across systems engineering, Core ML, Research, and Product teams to deliver unified SGP capabilities with architectural consistency. - Technical Translation & Requirements: Translate complex infrastructure metrics (LLM inference optimization, GPU utilization, compute orchestration) into actionable roadmaps. Map demands like multi-tenancy, data privacy, and isolation into platform features. - Risk & Dependency Mitigation: Proactively identify, track, and mitigate technical risks unique to massive-scale GenAI infrastructure and global SGP deployments, maintaining momentum despite fast-evolving AI frameworks. - Developer Velocity & Operational Excellence: Establish lightweight agile processes that empower engineers to ship fast without breaking core systems. Define and enforce clear SLOs and performance benchmarks to guarantee production-grade reliability for clients. - Metrics-Driven Adoption: Track and report on SGP adoption metrics, system reliability, delivery forecasts, and engineering bottlenecks directly to executive leadership to ensure the platform scales responsibly. Minimum Qualifications - 5+ years of experience as a Technical Program Manager, Product Manager, or Software Engineer, with a proven track record of having built and shipped technical products or platforms from scratch (e.g., internal cloud infrastructure, developer APIs, distributed systems, or ML platforms). - Platform Domain Expertise: 3+ years of dedicated experience managing programs focused directly on core engineering infrastructure, cloud-native ecosystems (AWS/GCP), container orchestration (Kubernetes), or distributed systems. - AI/ML Infrastructure Literacy: Foundational understanding of the infrastructure required for the Generative AI lifecycle, including high-throughput data pipelines, GPU/CPU cluster utilization, or model training/evaluation setups. - Masterful Communication:&l

ABOUT THE TEAM Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats to global security https://openai.com/index/updating-our-preparedness-framework/ that could scale to an extreme level of severity. Our work involves: 1. Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. 2. Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. 3. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework https://openai.com/index/updating-our-preparedness-framework/, and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. ABOUT THE ROLE Models are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world. As we push toward AGI, cybersecurity becomes one of the most important and urgent frontiers: the same systems that can accelerate productivity can also accelerate exploitation. As a Researcher for cybersecurity risks, you will help design and implement an end-to-end mitigation stack to reduce severe cyber misuse across OpenAI’s products. This role requires strong technical depth and close cross-functional collaboration to ensure safeguards are enforceable, scalable, and effective. You’ll contribute directly to building protections that remain robust as products, model capabilities, and attacker behaviors evolve. IN THIS ROLE, YOU WILL: - Design and implement mitigation components for model-enabled cybersecurity misuse—spanning prevention, monitoring, detection, and enforcement—under the guidance of senior technical and risk leadership. - Integrate safeguards across product surfaces in partnership with product and engineering teams, helping ensure protections are consistent, low-latency, and scale with usage and new model capabilities. - Evaluate technical trade-offs within the cybersecurity risk domain (coverage, latency, model utility, and user privacy) and propose pragmatic, testable solutions. - Collaborate closely with risk and threat modeling partners to align mitigation design with anticipated attacker behaviors and high-impact misuse scenarios. - Execute rigorous testing and red-teaming workflows, helping stress-test the mitigation stack against evolving threats (e.g., novel exploits, tool-use chains, automated attack workflows) and across different product surfaces—then iterate based on findings. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have a passion for AI safety and are motivated to make cutting-edge AI models safer for real-world use. - Bring demonstrated experience in deep learning and transformer models. - Are proficient with frameworks such as PyTorch or TensorFlow. - Possess a strong foundation in data structures, algorithms, and software engineering principles. - Are familiar with methods for training and fine-tuning large language models, including distillation, supervised fine-tuning, and policy optimization. - Excel at working collaboratively with cross-functional teams across research, security, policy, product, and engineering. - Have significant experience designing and deploying technical safeguards for abuse prevention, detection, and enforcement at scale. - (Nice to have) Bring background knowledge in cybersecurity or adjacent fields. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectr

As a Technical Program Manager , you will partner with our Frontier Agent Engineering teams on enterprise customer engagements — owning operational execution and delivery of our technical work by managing timelines, milestones, risks, and dependencies across technical deliverables. You will drive the strategic alignment and end-to-end execution of our most critical Enterprise initiatives. This is a high-leverage, technical leadership role where you will own program delivery from initial scoping to measurable, enterprise-wide adoption. You will serve as the core communication backbone and connective tissue between engineering, product, and executive leadership. You are not just managing timelines; you are accountable for systemic, measurable outcomes, driving efficiency across the full agentic application development process. Operating in a hyper-growth, demanding AI environment, you will translate technical complexity into clear execution strategies, proactively mitigate risks, and ensure our engineering teams deliver reliable, high-value solutions at scale. Key Responsibilities - End-to-End Program Ownership: Own the strategic planning, scheduling, and high-velocity execution of multiple enterprise-grade programs, ensuring on-time delivery against aggressive product goals. Run weekly cross-functional syncs, surface blockers, drive decisions. - Cross-Functional Architecture Integration: Manage complex dependencies and technical communication across core teams (e.g., Platform, Forward Deployed Engineering, Product) to seamlessly deliver frontier agents to our enterprise customers. - Technical Translation & Executive Influence: Synthesize deep technical complexities into concise, actionable insights for both engineers and C-suite stakeholders. Drive absolute clarity across the delivery team regarding priorities, risks, and strategic outcomes. - Risk & Dependency Mitigation: Proactively identify, track, and architect mitigations for technical risks unique to enterprise AI deployment, maintaining momentum in the face of ambiguity. - Process Evolution: Modernize and scale agile execution frameworks (e.g., Jira, Linear) to support rapid, iterative machine learning and software development lifecycles. - Metrics-Driven Accountability: Define, track, and report on key program health metrics, delivery forecasts, and engineering bottlenecks directly to executive leadership. Minimum Qualifications - 5+ Enterprise-Scale Experience: 5+ years of experience as a Technical Program Manager or in a technical leadership role managing complex, large-scale software engineering or machine learning development projects. - Engineering Domain Expertise: 2+ years of dedicated experience managing programs focused directly on core engineering infrastructure, platform services, or distributed systems. - AI/ML Literacy: Strong foundational understanding of the Generative AI lifecycle, including LLM utilization for structured downstream tasks, model fine-tuning, and performance evaluation. - Masterful Communication: Proven track record of presenting to and influencing executive-level stakeholders, with the ability to translate complex technical challenges into clear business impacts. - Execution Excellence: Advanced proficiency with iterative

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability. You will: - Own large new areas within our product - Work across backend, frontend, and interacting with LLMs and ML models - Deliver experiments at a high velocity and level of quality to engage our customers - Work across the entire product lifecycle from conceptualization through production - Be able, and willing, to multi-task and learn new technologies quickly Ideally you'd have: - 7+ years of full-time engineering experience, post-graduation - Experience scaling products at hyper growth startups - Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies - Proficient in Python or Javascript/Typescript, and SQL - Experience with Kubernetes - Experience with major cloud providers (AWS, Azure, GCP) Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $252,000 - $315,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-sta