Senior Research Engineer (Code World Models)

JetBrains

At JetBrains, code is our passion. Ever since we started, back in 2000, we've been striving to make the strongest, most effective developer tools on earth. Today, AI-powered coding agents are becoming a core part of how developers write Kotlin – and we want to make sure they write it well. The Kotlin AI Value Stream team is responsible for how AI agents understand, generate, and improve Kotlin code across all platforms: Android, Kotlin Multiplatform, server-side, web, desktop, and others. We build the evaluation infrastructure, error analysis tools, and post-training pipelines that measure and improve agent behavior on real Kotlin developer tasks. As a Research Engineer on this team, you'll own the end-to-end loop: Analyze how agents fail on Kotlin → build evals that capture those failures → research and implement methods to fix them → measure the improvement. Your work will directly shape how millions of developers experience Kotlin through AI coding agents. AS PART OF OUR TEAM, YOU WILL: Build tools for agentic error analysis * Design and implement tooling to systematically capture, classify, and analyse errors that AI coding agents make when generating Kotlin code. * Build observability pipelines over agentic traces – mining patterns from agent sessions in JetBrains IDEs, Junie, Claude Code, Cursor, and other coding agents. Build evaluation pipelines * Design, implement, and maintain evaluation pipelines that measure Kotlin code generation quality across dimensions, including correctness, idiomaticity, build success, framework usage, and test coverage. * Build simulation environments where coding agents can be measured on realistic Kotlin developer tasks – from greenfield KMP projects and Gradle dependency management to migrating Spring applications from Java to Kotlin. * Own evaluation infrastructure: metrics, experiment tracking, automated regression checks, and reproducible benchmarking. Research methods for improving agent and model behavior on Kotlin * Experiment with post-training techniques (SFT, DPO, GRPO) to improve how models handle Kotlin-specific patterns, idioms, and frameworks. * Investigate context engineering approaches: CLAUDE.md/AGENTS.md files, compiler-as-verifier feedback loops, Kotlin LSP integration, and MCP-based tooling. * Run experiments to measure impact: A/B comparisons, benchmark suites, and before/after analyses on real codebases. * Collaborate with model providers (Anthropic, OpenAI, and Google) to translate Kotlin-specific findings into model improvements. Build public Kotlin benchmarks * Design and build open-source benchmarks that measure AI coding agent performance on Kotlin tasks and eventually become the standard reference for the ecosystem. * Create task datasets covering the breadth of Kotlin usage: the server side (Spring, Ktor), multiplatform projects (KMP), build systems (Gradle), Android, library development, and others. * Include both mined real-world tasks and carefully designed synthetic tasks that test specific Kotlin capabilities. * Maintain and evolve benchmarks as models improve, ensuring they remain challenging, relevant, and contamination-resistant. WE'LL BE HAPPY TO HAVE YOU ON BOARD IF YOU HAVE: * Hands-on experience building evaluation or analysis pipelines for LLMs or AI coding agents in a research or production setting. * Strong Python engineering skills (at least three years), with the ability to write clean, maintainable code in data-heavy and ML-adjacent codebases. * Experience with data analysis at scale: querying large datasets (SQL/Athena), building data pipelines, and performing statistical analysis of experimental results. * The ability to own projects end to end – from identifying a problem in agent traces to designing an eval, running experiments, and shipping a fix. * A product-aware mindset: You care about how agents are actually used by developers and can translate real failure modes into evaluation and training work. * Familiarity with Kotlin or a strong willingness to develop deep Kotlin expertise (you'll be living in Kotlin codebases daily). OUR IDEAL CANDIDATE WOULD ALSO HAVE EXPERIENCE WITH: * Post-training LLMs: SFT, RLHF, DPO, GRPO – either hands-on training or designing the data and reward pipelines that feed into training. * Modern deep learning frameworks (PyTorch) and LLM training stacks (TRL, verl, Megatron, or similar). * AI agent development: tool-using agents, multi-step coding workflows, agentic frameworks. * Evaluation frameworks and tools: Inspect AI, Promptfoo, LM-evaluation-harness, or custom eval pipelines. * Experiment tracking and observability: Weights & Biases, MLflow, Langfuse, or similar. * The Kotlin ecosystem: Android, Gradle, KMP, Spring, Ktor – with an understanding of the developer workflows that agents need to support. * Contributing to or maintaining open-source projects, especially benchmarks or evaluation tools. Don't check every box? That's okay – if you're excited about this work and bring strong fundamentals, we'd love to hear from you. We're happy to talk and provide the training you need to grow into the role. WHY JOIN JETBRAINS?  * Strong base salary. We offer competitive pay that reflects your skills and experience. * Flexible work location. Enjoy the freedom to work from home or from the office. * Remote work. Spend up to 30 days per year working remotely from abroad. * Extra time off. More days to relax, recharge, and do the things you love. * Medical insurance allowance. Enjoy peace of mind for you and your family * Learning and development opportunities. Access to conferences, courses, and language classes. * Relocation support. We help make your move as smooth and stress-free as possible.  * Language classes. Pick up the local language or sharpen your English skills. * Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays. * Mental health support. To help you feel your best, we provide easy access to professional mental health services. * Sports benefit. Enjoy an on-site gym or sports club stipend. * Internal events. Join company-wide celebrations and team gatherings. *Some benefits may vary depending on location. #LI-KP1 We are an equal opportunity employer We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation. We process the data provided in your job application in accordance with the Recruitment Privacy Policy.

Adyen

THIS IS ADYEN Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition.  For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. AI RESEARCH Adyen is building a world-class AI team to redefine what intelligent systems can do in financial technology. As a Senior AI Research Engineer, you will take on some of the most technically demanding work in applied AI: designing agents that reason over complex, multi-step tasks; building the evaluation infrastructure that makes those systems trustworthy in production; and shaping how humans and AI collaborate at scale within a global payments company. This is not a narrow research role. You will take full ownership of your work, from early research through deployed production systems, influence the team's technical direction, and act as a force multiplier for the broader AI organization — including contributing to custom model development for structured financial data, and working toward our longer-term ambition of defining how humans and AI collaborate at scale across the company. WHAT YOU'LL DO * Design and Deploy AI Agents for Complex Tasks: Lead the research, design, and deployment of AI agents built for long-horizon, multi-step tasks in real-world financial contexts — including data analysis pipelines, operational workflows, and integrity risk scenarios. Architect robust agentic systems covering multi-agent orchestration, tool dispatch, context and memory management, and error recovery for long-running workflows. Design human-in-the-loop mechanisms that define when agents act autonomously, when they surface uncertainty, and when they escalate or defer to humans. * Own Evaluation and Benchmarking: Define and lead the evaluation strategy for the agentic systems and LLMs your team builds and deploys. Design internal benchmarks grounded in real domain complexity — probing for genuine capabilities, edge cases, and failure modes that standard metrics miss. Build reusable evaluation infrastructure that is embedded in the development process, not bolted on after the fact. * Provide AI Expertise Across the Organization: Serve as a technical resource for AI initiatives across Adyen — evaluating agentic frameworks, retrieval and search strategies, or agent tool-use approaches across partner teams. Surface connections across initiatives and help teams avoid duplicating work or converging on the wrong approach. * Raise the Bar: Set engineering standards for the team and company. Provide mentorship through problem decomposition, research methodology, and code review. Champion reproducibility, documentation, and rigorous evaluation practices across the AI organization. WHO YOU ARE * You have 6+ years of hands-on experience in applied AI/ML research or engineering, with a clear track record of shipping AI systems, including agentic or LLM-powered systems, in production environments. * You have deep expertise in language models and Generative AI, with hands-on depth across several of: architecture, post-training (fine-tuning, RLHF), inference optimization, context engineering, and failure modes at scale. * You have proven experience designing and operating agentic systems at scale, multi-agent orchestration, tool use, memory and context management, state handling for long-running workflows, and human-in-the-loop design. You understand what separates production agents from research prototypes. * You are rigorous and systematic about evaluation. You have designed evaluation frameworks or internal benchmarks that go beyond standard metrics. You understand the failure modes of LLM-as-judge approaches and know how to measure what actually matters for a given system and use-case. * You have a strong foundation in classical machine learning: supervised learning, ensemble methods, optimization, probabilistic modeling, and statistics. You reach for the appropriate tool for the problem. * You write clean, well-structured, production-ready code, primarily Python, and you hold research code to an engineering standard. * You have hands-on experience with at least one production-grade agentic framework. NICE TO HAVE (TELL US ABOUT THEM!) * Any experience with tabular deep learning architectures * Familiarity with financial data, payments, fraud detection, or risk systems. * Track record of external visibility: publications, conference presentations, or open-source contributions. * Experience with observability and evaluation tooling. * Familiarity with MLOps and model deployment pipelines in large-scale environments. Our Diversity, Equity and Inclusion commitments  Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum. Our business and technical challenges are unique, and we need as many different voices as possible to join us in solving them - voices like yours. No matter who you are or where you’re from, we welcome you to be your true self at Adyen.  Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application! What’s next? Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don’t be afraid to let us know if you need more flexibility.   This role is based out of our Madrid office. We are an office-first company and value in-person collaboration; we do not offer remote-only roles. We'll cover your relocation if you want to live in our wonderful, sunny, and bright city.

Isomorphic Labs

Isomorphic Labs is applying frontier AI to help unlock deeper scientific insights, faster breakthroughs, and life-changing medicines with an ambition to solve all disease. The future is coming. A future enabled and enriched by the incredible power of machine learning. A future in which diseases are curtailed or cured starting with better and faster drug discovery.  Come and be part of an interdisciplinary team driving groundbreaking innovation and play a meaningful role in contributing towards us achieving our ambitious goals, while being a part of an inspiring and collaborative culture. The world we want tomorrow is the one we’re building today. It starts with the culture at this company. It starts with you.    ABOUT ISO Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-winning AlphaFold system. Since then, our interdisciplinary team of drug discovery experts and machine learning specialists has built powerful new predictive and generative AI models that accelerate scientific discovery at digital speed. Our name comes from the belief that there is an underlying symmetry between biology and information science. By harnessing AI’s powerful capabilities, we can use it to model complex biological phenomena to help design novel molecules, anticipate how drugs will perform and develop innovative medicines to treat and cure some of the world’s most devastating diseases. We have built a world-leading drug design engine comprising AI models that are capable of working across multiple therapeutic areas and drug modalities. We are continually innovating on model architecture and developing cutting-edge capabilities to advance rational drug design. Every day, and with each new breakthrough, we’re getting closer to the promise of digital biology, and achieving our ambitious mission to one day solve all disease with the help of AI.   RESEARCH ENGINEERING (MACHINE LEARNING), LONDON  We are looking for Research Engineers with different levels of experience - Mid through to Senior, Staff, Principal or equivalent levels. YOUR IMPACT  This is an exciting opportunity for you to contribute to frontier research at the intersection of AI and drug design. Working in a highly creative, iterative environment, you will be partnering with scientists and engineers to advance foundational models that will transform the biopharmaceutical world as we know it.   You will draw upon your existing engineering and Machine Learning experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems. WHAT YOU WILL DO  Implementation & Optimisation: * Translate research concepts into practical implementations by developing and optimising state-of-the-art AI models, and building and maintaining robust codebases, data pipelines, and infrastructure for training and evaluation. Experimentation & Evaluation: * Design, implement, and run experiments to evaluate the performance and robustness of ML models, using a full spectrum of state-of-the-art machine learning methods. Evaluating, tuning, and maintaining AI/ML models (which includes collecting and preparing data as needed) Evaluation & Inference: * Implement algorithms and software to analyse and evaluate the performance of AI models. * Optimising performance of AI/ML models such as Diffusion models, Transformers, GNNs, leveraging a deep understanding of the AI/ML hardware+software stack * Advise on how to bring AI/ML models to production and/or integrating them into product offerings, and monitoring and refining their behavior. * Developing specialised tools/frameworks/infrastructure to aid in the work above Collaboration & Knowledge Sharing: * Work closely with research scientists and engineers, contributing to team discussions, sharing knowledge, and actively participating in code reviews to foster a collaborative environment. Innovation & Impact: * Proactively identify and address technical challenges, stay updated on the latest AI advancements, and focus on developing solutions that enable scaling our wider foundation and applied model platforms. * Ability to execute on independent engineering projects and software development towards research goals. SKILLS AND QUALIFICATIONS ESSENTIAL * Academic Background: Advanced degree (Master’s or PhD) in a highly quantitative field (Computer Science, AI, Physics, Mathematics, etc.) or equivalent practical experience. * ML Fundamentals: Deep understanding of machine learning principles and techniques. * Framework Expertise: Strong proficiency in deep learning frameworks such as JAX or PyTorch. * Modern Architectures: Hands-on experience building and working with modern model architectures (e.g., Transformers, GNNs, Diffusion Models). * Full ML Lifecycle: Experience taking models from conception to production (scoping, data analysis, training, debugging, evaluation, benchmarking, and deployment). * Engineering Excellence: Excellent software development skills with strong algorithms and data structures fundamentals. * Collaboration & Communication: An excellent team player with strong written and verbal communication skills, able to collaborate seamlessly in a cross-disciplinary environment. * Agency: Self-directed with an ability to navigate ambiguity, propose and own complex projects, learn the necessary context, and readily adapt to new domains and developments. Nice to have * Proven Research Record: A history of scientific contributions (e.g., publications at NeurIPS, ICML, ICLR, CVPR) or significant contributions to state-of-the-art AI models. * Scale & Performance: Experience training models across distributed systems (multi-GPU/multi-node) and optimising training and inference performance (e.g., XLA, Triton, CUDA, Pallas). * Domain Knowledge: A strong interest in, or knowledge of, biochemistry, computational biology, or drug discovery fundamentals. * Industry Experience: Proven track record working in reputable tech companies or research labs. * Applied ML: Experience developing models developed for real-world applications. * Infrastructure: Solid technical infrastructure knowledge and experience with low-level engineering (e.g., GCP, Kubernetes, Docker) CULTURE AND VALUES We are guided by our shared values. It's not about finding people who think and act in the same way. These values help to guide our work and will continue to strengthen it.  Thoughtful Thoughtful at Iso is about curiosity, creativity and care. It is about good people doing good, rigorous and future-making science every single day. Brave Brave at Iso is about fearlessness, but it’s also about initiative and integrity. The scale of the challenge demands nothing less. Determined Determined at Iso is the way we pursue our goal. It’s a confidence in our hypothesis, as well as the urgency and agility needed to deliver on it. Because disease won’t wait, so neither should we. Together Together at Iso is about connection, collaboration across fields and catalytic relationships. It’s knowing that transformation is a group project, and remembering that what we’re doing will have a real impact on real people everywhere. CREATING AN EXTRAORDINARY COMPANY We believe that to be successful we need a team with a range of skills and talents. We're building an environment where collaboration is fundamental, learning is shared and every employee feels supported and able to thrive. We value unique experiences, knowledge, backgrounds, and perspectives, and harness these qualities to create extraordinary impact. We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding) or any other basis protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know. HYBRID WORKING It’s hugely important for us to share knowledge and build strong relationships with each other, and we find it easier to do this if we spend time together in person. This is why we follow a hybrid model, and would require you to be able to come into the office 3 days a week (currently Tuesday, Wednesday, and one other day depending on which team you’re in). If you have additional needs that would prevent you from following this hybrid approach, we’d be happy to talk through these if you’re selected for an initial screening call. Please note that when you submit an application, your data will be processed in line with our privacy policy. >> Click to view other open roles at Isomorphic Labs