{"id":4278948,"url":"https://alion.io/job/physicsx-ai-engineer-evals","title":"AI Engineer: Evals","company":{"id":251,"name":"PhysicsX","domain":"physicsx.ai","url":"https://alion.io/company/physicsx","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":83,"open_postings":40,"ghost_share":0.2,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":98,"computed_at":"2026-11-12T10:38:37Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"on_site","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":"LLM","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Post-training","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Synthetic Data","optional":true}],"status":"live","first_seen_at":"2026-11-13T14:32:20Z","employer_posted_date":"2026-11-13","last_verified_at":"2026-11-13T19:53:59Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About us\nRe-architecting Engineering for the Age of Intelligence\n\nPhysicsX is the physics AI company for industrials. The company’s mission is to accelerate hardware innovation by overhauling what industrial engineering and manufacturing look like today. PhysicsX is building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle. The company partners with leading organisations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables, supporting them on some of their most critical and complex challenges. PhysicsX is headquartered in the United Kingdom, with offices in London, New York, and Singapore and an expanding presence in the Bay Area.\nThe role\nYou will build the evaluation discipline that lets teams design, deploy and improve trustworthy agents in production. You will report into the overall engineering lead for our Agentic strategy.\nThis is a hands-on engineering role with an organisation-wide mandate. Product, delivery and customer teams own the evals for the agents they ship. You will give them the shared infrastructure, frameworks, practices and coaching to do that well. You will also own cross-product evaluation and develop public benchmarks for agents doing real engineering work.\nWhat you will do\nLead the technical strategy and implementation of how PhysicsX evaluates agents.\nBuild reusable evaluation frameworks, reference implementations and golden paths on top of our existing tooling.\nHelp product, delivery and customer teams establish robust eval suites, then turn what works into repeatable guidance.\nDevelop datasets and evaluators that combine deterministic checks, domain-expert judgement, model-based grading and human review.\nConnect offline evaluation, regression testing and production telemetry so teams can detect drift and learn from real use.\nDefine cross-product scorecards and shared benchmarks without taking ownership away from the teams shipping each agent.\nCreate and publish credible open benchmarks for agents performing real engineering and manufacturing workflows.\nWork with Research and Post-Training on model and agent evaluation. Own cross-product, production-agent and public benchmark integrity; share approval when results support product or external claims.\nBuild institutional muscle through reviews, examples, training and direct collaboration, making rigorous evaluation part of how teams think rather than a final release step.\nHelp determine how this capability should grow and, over time, shape the team around it.\nWhat you bring\nWhere you need to be strongest\nYou have built and operated evaluation systems for agents or LLM-powered products in production.\nYou can turn an ambiguous product goal into datasets, evaluators, experiments and decision criteria that teams trust.\nYou understand the failure modes of probabilistic systems and use appropriate statistical judgement rather than treating benchmark scores as exact.\nYou know when to use deterministic evaluators, domain experts, human review and LLM-as-a-judge, including the limitations of each.\nYou are a strong engineer who builds usable frameworks and production-quality tooling, not only analyses or notebooks.\nYou have helped multiple teams adopt a technical practice through hands-on delivery, clear standards and pragmatic coaching.\nYou can work directly with customers and domain experts, learn what correctness means in their workflows and encode it without losing important nuance.\nFoundations\nEvaluation of multi-step agents, tool calls, structured outputs and long-running workflows.\nTrace-based observability and OpenTelemetry concepts.\nDataset design, sampling, experiment design, regression detection and reproducibility.\nCI and release gates for systems whose behaviour is non-deterministic.\nClear technical writing and communication across product, research, engineering, delivery and customer teams.\nProduct judgement: knowing which measurements should drive a decision and which are merely interesting.\nNice to have\nExperience with Pydantic Evals, Pydantic Logfire or comparable code-first evaluation and observability tools.\nExperience evaluating agents in engineering, simulation, design, manufacturing or other expert domains.\nExperience creating public benchmarks or open-source evaluation tooling.\nFamiliarity with post-training, synthetic data, reward signals or model selection.\nExperience in regulated, customer-operated or air-gapped environments.\n\nWe value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics. \nWe collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with employment and equality legislation. 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