{"id":1308582,"url":"https://alion.io/job/matter-intelligence-data-infra-signals-and-evaluations-ic","title":"Data Infra - Signals and Evaluations (IC)","company":{"id":2179048,"name":"Matter Intelligence","domain":"matter.com","url":"https://alion.io/company/matter-com","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":4,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-04T06:34:25Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":136000,"max_usd":296000,"period":"year","method":"role_country_seniority_unknown","sample_n":3718},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Function Calling","optional":false},{"name":"Imitation Learning","optional":false},{"name":"JAX","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Synthetic Data","optional":false},{"name":"World Models","optional":false}],"status":"live","first_seen_at":"2026-09-15T01:10:31Z","employer_posted_date":"2026-09-15","last_verified_at":"2026-11-04T17:04:24Z","board_verified":true,"closed_at":null,"days_open":50,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":50},"description":"About Matter Intelligence\nWelcome to Matter, where we are building the future of vision AI: pairing a world-first sensor that sees molecular chemistry, temperature, and 3D shape with a Large World Model that will be the most powerful intelligence engine for the physical world. This system doesn't just see what something looks like; it understands everything from a single pixel. We call this Superintelligent Vision.\nOur team has delivered technologies to Mars for NASA/JPL, designed advanced sensors for U.S. Defense, and frontier artificial intelligence systems. We are now building the next generation of space- and airborne-based sensing systems.\nAbout the Role\nMatter is hiring a Signal, Data, and Evaluation Engineer to build the datasets, benchmarks, environments, and evidence that make our models and AI systems scientifically defensible. Reporting to Ignacio Cases Martin, this individual contributor will work across data curation, simulation and learning environments, model and agent evaluation, and release-quality evidence.\nKey Responsibilities\nBuild versioned dataset workflows for collection, curation, filtering, labeling, ground truth, synthetic data, hard-negative mining, contamination controls, and train-evaluation isolation.\n\nDesign benchmark suites across perception, multimodal reasoning, physics-informed prediction, retrieval, planning, tool use, world modeling, and customer tasks.\n\nCreate simulation and environment infrastructure for reinforcement learning, imitation learning, offline learning, model-based learning, and agent training.\n\nDefine repeatable evaluation methods across accuracy, calibration, generalization, robustness, safety, latency, cost, and operational outcomes.\n\nTurn field, mission, and customer failures into versioned datasets, benchmark cases, adversarial tests, and environment scenarios.\n\nBuild automated promotion gates and communicate clearly what has been tested, what remains unproven, and what evidence supports release.\n\nQualifications\nRequired\nExperience in ML evaluation, dataset engineering, reinforcement-learning environments, simulation, scientific ML, test infrastructure, or production AI systems.\n\nStrong foundations in statistics, experimental design, benchmark validity, distribution shift, calibration, reward design, and evidence-based acceptance.\n\nFluency in Python and modern machine-learning frameworks, with the software engineering discipline to build tested modules, data contracts, or services.\n\nExperience converting qualitative model or agent failures into reproducible datasets, tests, or environment scenarios.\n\nAbility to reason across the complete data path and identify how acquisition, transformation, indexing, orchestration, and presentation affect correctness.\n\nPreferred\nExperience with dataset curation, benchmark platforms, deep reinforcement learning, world models, synthetic data, multimodal evaluation, or scientific validation.\n\nExperience with PyTorch or JAX, distributed evaluation, experiment tracking, environment frameworks, or model and agent observability.\n\nExperience with uncertainty quantification, calibration, out-of-distribution detection, conformal methods, or selective prediction.\n\nExperience evaluating models deployed to aircraft, satellites, robotics, industrial systems, or other constrained environments.\n\nWhat Success Looks Like\nModel and agent releases are supported by reproducible datasets, benchmarks, and clearly stated evidence.\n\nFailures from experiments and deployments become durable test cases that improve future systems.\n\nEvaluation results preserve scientific meaning and make capability, uncertainty, and residual risk legible to the team.\n\nLocation\nThis role is based in San Francisco, CA, and requires onsite work.\nITAR Requirements\nTo comply with U.S. export regulations, applicants must be one of the following:\nA U.S. citizen or national\n\nA lawful permanent resident (green card holder)\n\nEligible to obtain required authorizations from the U.S. Department of State\n\nEmployee Offerings and Benefits\nAt Matter, we believe in rewarding high performance and providing the support you need to thrive. Our compensation and benefits package includes:\nCompetitive compensation based on experience\n\nEarly-stage equity package\n\n100% employer-paid health, dental, and vision coverage\n\nOpportunity to work on novel sensing, data, and AI systems with real-world deployment paths to the largest industries in the world\n\nMatter Intelligence is an equal opportunity employer. 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