Research Engineer, Human Understanding

Research Engineer

Relation Therapeutics

ABOUT RELATION Relation is a sector defining TechBio company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure. We are scaling rapidly and building a team of exceptional individuals to push the boundaries of drug discovery. You will work in highly interdisciplinary teams where biology, computation, and engineering come together to solve complex problems that have not been solved before. Our state-of-the-art wet and dry labs in the heart of London are designed to accelerate this integration and translate insight into impact. We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients. THE OPPORTUNITY Join our machine learning group as a Research Engineer and help drive the development, deployment, and scaling of ML and computational systems across the company. You’ll work at the intersection of research and engineering—improving research workflows, supporting rapid experimentation, and enabling teams to push the limits of modern ML. You’ll collaborate with machine learning scientists, data scientists, platform engineers, and other domain experts across the organisation. Depending on priorities, you may work within a specific ML team or operate in a cross-functional capacity. Based at our wet/dry lab and headquarters in central London, you’ll tackle challenges involving large datasets, complex models, and high-performance compute. Your work will strengthen our training and inference pipelines, improve our software foundations, and optimise our hybrid on-prem/cloud environment, which includes dedicated DGX clusters and collaboration with partners like NVIDIA. This role offers a chance to shape the systems and tools that power cutting-edge ML research. DAY TO DAY, YOU WILL * Work with interdisciplinary teams to solve challenges across data engineering, ML engineering, and software engineering. * Build and improve data processing, transformation, and loading systems to support model training and inference at scale. * Develop and maintain high-quality research and production codebases to enable rapid, reproducible experimentation. * Advance our software engineering practices by optimising systems, streamlining pipelines, and improving robustness across workflows. PROFESSIONALLY, YOU WILL HAVE * BSc/MSc/PhD in CS/ML/Engineering (or related), 2+ years industry experience. * Solid understanding of algorithms, data structures, complexity. * Proficiency in Python with clean, maintainable coding practices. * Familiarity with PyTorch and common scientific Python libraries. * Solid understanding of ML fundamentals and modern deep learning. * Experience training, evaluating, and iterating on models. * Familiarity with AWS/GCP, Docker, Kubernetes, and CI/CD. * Familiarity with orchestration tools (Airflow/Prefect) and model-serving frameworks. Bonus experience * Exposure to biology/bioinformatics or ML for scientific domains. PERSONALLY, YOU * Are comfortable working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams. * Take ownership of your work, proactively seek opportunities to contribute, and enable others to do their best work. * Communicate openly and directly, give and receive feedback constructively, and handle challenging conversations with respect. * Actively seek out diverse perspectives, build strong working relationships, and contribute to shared goals across teams. * Embrace challenges with openness and resilience, set high standards for yourself, and strive to deliver meaningful outcomes. WORKING STYLE & CULTURE AT RELATION At Relation, we operate in a matrixed, interdisciplinary environment, where impact is driven through collaboration across scientific, technical, and operational domains. We collaborate, and you will partner with colleagues across multiple teams and projects, contributing your expertise while aligning to shared company priorities. We work together and win together! The patient is waiting! RECRUITMENT AGENCIES Please note that Relation does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation will not be liable for any fees associated with unsolicited CVs. Relation is a committed equal opportunities employer.

ML Research Engineer, London

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

Security Engineer & Researcher

Maze

SUMMARY OF THE ROLE: As a Security Research Engineer at Maze, you'll be at the forefront of defining what constitutes real security risk in the age of AI-powered vulnerability detection. This is a unique opportunity to join our growing security research team at a well-funded startup building at the intersection of generative AI and cybersecurity, where your security expertise directly shapes how our AI models understand and prioritize cloud security threats. You'll spend the majority of your time as the expert human-in-the-loop, analyzing cloud vulnerability findings from our AI systems, conducting deep research to validate and contextualize threats, and creating the authoritative labels that train our models to distinguish critical risks from noise. Working alongside other security researchers, you'll help scale our labeling operations while providing critical input into product development decisions based on real-world threat patterns you discover. This role is perfect for a security researcher who wants to pioneer the future of AI-assisted threat detection, loves diving deep into cloud security vulnerabilities, and wants to see their security insights amplified through cutting-edge technology while contributing to a growing team. YOUR CONTRIBUTIONS TO OUR JOURNEY: * Scale Expert Data Labeling Operations: Lead high-volume vulnerability labeling and validation work as the authoritative voice on threat severity, reviewing and categorizing cloud security findings from our AI models to create the high-quality training data that powers our platform * Drive Product Development Through Research Insights: Translate patterns and insights from your labeling and research work into actionable product improvements, working directly with engineering and product teams to enhance detection capabilities and user experience * Collaborate with Security Research Team: Work closely with fellow Security Research Engineers to maintain consistency in labeling standards, share research findings, and collectively improve our vulnerability assessment methodologies * Deep Vulnerability Research: Conduct comprehensive research into cloud vulnerabilities affecting EC2 images, Docker containers, and cloud infrastructure, investigating true/false positives, analyzing business impact, and building proof-of-concepts to validate threat scenarios * Enhance AI Model Accuracy: Provide expert feedback through our labeling tools that improves our AI models' understanding of vulnerability context, helping them learn to prioritize threats like a seasoned security researcher * Technical Investigation and Analysis: Create detailed technical writeups about exploitation techniques, attack vectors, and remediation strategies for cloud vulnerabilities, turning complex security research into actionable intelligence * Leverage External Security Intelligence: Integrate insights from CVE databases, security advisory feeds, and threat intelligence sources to enrich vulnerability findings with broader context and emerging threat patterns * Contribute to Thought Leadership: Support our external presence through technical blog posts, security videos/podcasts, and occasional conference presentations, sharing insights from your research WHAT YOU NEED TO BE SUCCESSFUL: * Security Research Expertise: 5+ years of hands-on security experience with proven vulnerability research background, comfortable investigating complex security issues and building proof-of-concepts to validate findings * Cloud Security Mastery: Deep knowledge of AWS security, cloud infrastructure vulnerabilities, container security, and cloud-native attack vectors, with hands-on experience securing cloud environments at scale * Technical Investigation Skills: Strong coding and scripting abilities (Python, Go, or similar) for automating research tasks, building validation tools, and creating proof-of-concept exploits * Analytical Excellence: Proven ability to analyze complex security data, distinguish between critical threats and false positives, and communicate technical findings to both technical and business audiences * Product Mindset: Experience translating security insights into product requirements, with ability to identify patterns across vulnerabilities that inform strategic product decisions * External Intelligence Integration: Experience working with vulnerability databases, security advisory feeds, and threat intelligence sources to contextualize and prioritize security findings * Collaborative Mindset: Strong communication skills and ability to work effectively with security research peers, AI/ML teams, and product stakeholders, translating security domain knowledge into actionable improvements * High-Volume Execution: Comfort with systematic labeling work while maintaining accuracy and attention to detail, balancing speed with quality in fast-paced environments * Nice to haves: * Experience with AI/ML security or working with AI-generated security findings * Background at security tooling companies or building security products * Expertise in specific vulnerability research methodologies and frameworks * Open source contributions to security tools or research projects * Previous content creation experience in security (blogs, talks, research papers) * Industry certifications (CISSP, OSCP, AWS Security, etc.) WHY JOIN US: * Ambitious Challenge: We're using generative AI (LLMs and agents) to solve some of the most pressing challenges in cloud security today. You'll be defining how AI understands and prioritizes vulnerabilities, working at the cutting edge of AI-powered threat detection. * Expert Team: We are a team of hands-on leaders with experience in Big Tech and Scale-ups. Our team has been part of the leadership teams behind multiple acquisitions and an IPO. * Growing Security Research Function: Join a collaborative security research team where you'll work alongside other experts, share insights, and collectively shape how our AI platform understands security threats at scale. * Impactful Work: Your security research and labeling work will directly improve how thousands of organizations understand and respond to cloud security threats, scaling expert security knowledge through AI to protect the entire ecosystem. * Product Influence: Your day-to-day research insights will directly influence product strategy and development, giving you a voice in building the next generation of AI-powered security tools. * Pioneer AI-Native Security: Help establish the gold standard for AI-assisted vulnerability research, defining how human security expertise enhances machine learning models in the cybersecurity domain.