{"id":3104580,"url":"https://alion.io/job/materiom-ai-engineer","title":"AI Engineer","company":{"id":1932512,"name":"Materiom","domain":"materiom.org","url":"https://alion.io/company/materiom","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","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":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"CrewAI","optional":false},{"name":"Diffusion Models","optional":false},{"name":"GCP","optional":false},{"name":"Google ADK","optional":false},{"name":"LLM","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Pydantic AI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SDL","optional":false},{"name":"World Models","optional":false},{"name":"C","optional":true}],"status":"live","first_seen_at":"2026-06-03T10:43:03Z","employer_posted_date":"2026-10-22","last_verified_at":"2026-11-04T21:17:53Z","board_verified":true,"closed_at":null,"days_open":154,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":153},"description":"Contract: Full-time, permanent\nLocation: Hybrid (London office)\nLevel: 2-4 years professional experience\nSalary: £70K+ depending on experience\nAbout Materiom\nMateriom's mission is to create a world where materials regenerate nature and support human health. We pursue it by building data and AI tools that help discover natural alternatives for packaging, textiles, and the built environment. We support innovators around the world to bring these new materials to market.\nWe're an interdisciplinary team bringing together materials engineering, computational materials science, AI/ML engineering, and business innovation. In 2026, we're at an inflection point: with advanced AI and a self-driving lab, we are accelerating the discovery of natural materials and supporting innovators across the sector. \nThe role\nThis is a high-impact role with the potential to apply leading AI/ML to one of the world's greatest challenges. We're looking for a mid-level AI Engineer to work at the intersection of applied ML and applied AI; someone equally comfortable developing predictive models on structured scientific data as they are with building LLM-powered tools and agentic workflows.\nYou'll work within our tech team to contribute across two primary workstreams:\nPredictive modelling & representation learning: contribute to the development and operationalization of ML models that learn the high-dimensional, multi-objective, natural polymers design space.\nMaterial discovery agentic systems: contribute to the development and evaluation of agentic systems for scientific discovery, interfacing with Materiom’s models, simulation capabilities, and internal and external self-driving labs.\nWhat you'll do\nML modeling\nDesign, build, and deploy structure-property prediction ML models of bio-based formulations from experimental, in-silico and literature-mined data. In pursuit of a base model that generalizes across materials systems.\nRun rigorous experiments to compare modelling approaches, interpret results clearly, and iterate toward quality goals.\nQuantify how confident models are in their predictions, and use that to decide which experiments or simulations to run next.\nWork with materials scientists to define new features and target properties, data standards and success criteria for each model.\nAgents for materials discovery\nContribute to Materiom’s agentic stack for scientific discovery, ranging from hypothesis generation to closing the loop with Materiom’s SDL and simulation engine.\nBuild tool interfaces, such as MCP servers, that give scientists and agents structured access to internal and external resources such as Materiom’s databases, predictive models, simulation engine and lab instruments.\nTrack developments in AI for science and agentic research, and prototype promising methods against Materiom’s use cases.\nMLOps\nDevelop, operate and maintain workflows for data extraction, model training & evaluation, and orchestration workflows against lab equipment/partners.\nContribute to LLMOps and MLOps best practices, including versioning, monitoring, evaluation, cost/quality optimisation.\nDeploy ML/AI-driven tooling to project partners, pilot users and beyond in order to gather user feedback.\nInternal & external-facing collaboration\nEffectively communicate complex technical concepts and findings to multidisciplinary audiences.\nWork closely within the tech team and stay closely attuned to product and scientific priorities, translating them into well-scoped technical work.\nWhat we're looking for\nYou'll need:\nGenuine excitement about the potential of transforming the materials sector through AI-enabled materials discovery of breakthrough bio-based alternatives.\nSolid grounding in ML fundamentals: statistical learning, neural networks, optimisation, model selection and validation, uncertainty estimation, and working with small, noisy or imbalanced datasets. \nPractical experience developing ML-powered systems end to end, from data curation, collection and preparation to model choice and hyperparameter tuning, to model deployment. You have experience with PyTorch, scikit-learn, MLFlow, etc.\nPractical experience building LLM-based agents, improving them through metrics-driven evaluation, ideally including research loops where agents propose, run and evaluate experiments to optimise agent performance or to develop ML models. You have experience with e.g. PydanticAI, CrewAI, Google ADK etc.\n Familiarity with at least one advanced deep learning technique such as geometric learning (equivariant GNNs), spatio-temporal techniques (SSMs, neural ODEs), world models (JEPA, latent dynamics models), language modeling (chemical and protein LMs), diffusion models, or physics-informed neural networks (PINNs).\nMaster’s degree in a technical field (e.g., Computer Science, Artificial Intelligence, Machine Learning), plus 2 to 4 years of professional experience in an AI start up environment.\nStrong Python skills and good software engineering habits: version control, testing, reproducible pipelines.\nFamiliarity with a major cloud platform (e.g. GCP, AWS).\nExperience working in an environment that translates well into a small startup setting. You have high agency & autonomy in an ambiguous environment. You thrive at shipping progress without needing everything defined upfront.\nUseful but not required:\nProficiency in getting ML/AI-centric artefacts in front of users for obtaining real-world feedback.\nExperience with active learning or closed-loop experimentation workflows.\nFamiliarity with scientific data from chemistry, materials science, or adjacent domains.\nExperience with relevant open-source frameworks.\nBackground in or genuine curiosity about bio-based materials or sustainability.\nWhat We Offer\nMateriom is an impact-focused startup offering a supportive and flexible environment where you can drive the acceleration of net-positive materials using cutting-edge technology. Our benefits include\nCompetitive Salary: An annual salary range of £70K+, commensurate with your experience and expertise.\nAnnual Bonuses: Eligibility for performance-based bonuses to reward your contributions to the company’s success.\nGenerous Paid Time Off: 30 days of paid holiday per year for full-time positions (adjusted pro-rata for part-time positions), in addition to all UK bank holidays.\nLearning & Mentorship Grants: An annual individual budget dedicated to developing your hard and soft skills.\nCommuter Support: Access to a Bike2Work scheme to support sustainable travel.\nFlexible Hybrid Working: A highly flexible scheme that includes weekly days at the office (London) and at home, as well as options for temporary remote work.\nInternational Retreats: Regular company retreats, often held in international locations, to build connection and celebrate progress.\nCollaborative team culture: Our culture is defined by deep, interdisciplinary collaboration, offering you the exciting opportunity to work at the intersection of materials science and AI to drive positive impact for people and the planet","description_format":"text","description_chars":7039,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":["Annual bonuses","Hybrid work"],"hiring_locations":[{"name":"United Kingdom","iso":"GB","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Chemical Manufacturing","Generative 3D"],"lifecycle":[{"event":"open","at":"2026-10-22T18:37:16Z"}],"visa":[],"liveness":{"score":8,"band":"cold","label":"Long shot","p_open":1,"p_active":0.297,"p_room":0.28,"age_days":153,"expected_fill_days":30,"reasons":["conf:4","win:tail","crowd:"],"computed_at":"2026-11-04T06:34:25Z"},"pay":null,"html_url":"https://alion.io/job/materiom-ai-engineer","json_url":"https://alion.io/job/materiom-ai-engineer.json","meta":{"generated_at":"2026-11-04T21:49:10Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":235,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-05T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":1932512},"rest":"https://alion.io/mcp/rest/get_company?id=1932512"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fmateriom-ai-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fmateriom-ai-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fmateriom-ai-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/materiom-ai-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fmateriom-ai-engineer"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3104580}},{"tool":"search_jobs","arguments":{"company":"materiom.org","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3104580},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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