{"id":176067,"url":"https://alion.io/job/latent-labs-machine-learning-scientist","title":"Machine Learning Scientist","company":{"id":63173,"name":"Latent Labs","domain":"latentlabs.com","url":"https://alion.io/company/latent-labs","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":7,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-16T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false}],"status":"live","first_seen_at":"2026-06-29T14:43:21Z","employer_posted_date":"2026-06-29","last_verified_at":"2026-10-16T19:09:07Z","board_verified":true,"closed_at":null,"days_open":109,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":108},"description":"The Opportunity\nWe are looking for a highly skilled machine learning researcher with significant experience in generative modeling. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will architect novel generative models with the goal of designing new proteins that are functional in wet lab assays.\nWho you are\nYou are a strong ML researcher with experience in generative modeling. You have led or worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a proven track record of deep expertise in generative modeling.\n\nYou are a skillful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience running training and inference on cloud hardware, parallelizing data and models across accelerators.\n\nYou are a data engineer. You have experience building ML data pipelines for the training and evaluation of deep learning models. You are able to analyze the raw data, construct appropriate dataset splits and build pipelines that perform and scale.\n\nYou are passionate about model performance. You have an intricate understanding of how ML libraries interplay with hardware and data and love to optimize deep learning models for training / inference speed. You have a deep knowledge of best principles and tricks in architecting deep learning models and use it to optimize how they perform on validation metrics.\n\nYou are mission driven and curious. You are passionate about making a positive impact on the world, whether it's for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear. You thrive in a dynamic environment. You work well in a fast-paced setting where goals must be achieved efficiently and urgently.\n\nWhat sets you apart\nYou have experience in computational biology or protein design. You have worked on ML-driven projects in biology.\n\nYou have a natural science background. You are academically trained in physics, biology, chemistry or other related fields.\n\nYour Responsibilities\nBuild machine learning models that work in the physical world [~90% of your time]:\nContribute to a careful curation of our training and evaluation data.\n\nPropose and build ML evaluation metrics that align with real world success and company goals.\n\nQuickly prototype generative models against our lead metrics and perform deep analyses of improvements.\n\nCollaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.\n\nContribute to the maintenance of our compute and ML development infrastructure.\n\nIn collaboration with the bio team, plan wet lab testing campaigns and carry out model inference against biological targets to enable their testing in the wet lab.\n\nQuickly learn from wet lab results and feedback data to our models.\n\nSelf development [~10% of your time]:\nStay on top of the latest developments in ML.\n\nGain a strong working understanding of protein and cell biology.\n\nParticipate in knowledge sharing, e.g. organize and present at our internal reading group.\n\nAttend and present at conferences.\n\nApply\nWe offer strongly competitive compensation and benefits packages, including:\nPrivate health insurance\n\nPension/401(K) contributions\n\nGenerous leave policies (including gender neutral parental leave)\n\nHybrid working\n\nTravel opportunities and more\n\nWe also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.\nWe welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and 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