{"id":1745271,"url":"https://alion.io/job/advancedspace-machine-learning-engineer-5-8-yrs","title":"Machine Learning Engineer (5-8 yrs)","company":{"id":7135,"name":"Advancedspace","domain":"advancedspace.com","url":"https://alion.io/company/advancedspace","size_band":"11-50","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":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Westminster, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":124000,"max":171000,"currency":"USD","period":"year","gross":null,"usd_annual":171000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"JAX","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"TensorFlow","optional":false},{"name":"Digital Twin","optional":true},{"name":"Sim-to-Real","optional":true}],"status":"live","first_seen_at":"2026-10-02T16:09:26Z","employer_posted_date":"2026-10-02","last_verified_at":"2026-10-06T20:37:32Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Advanced Space | Machine Learning Engineer (5-8 Years) | Full-time | Hybrid\nWe’re going to the Moon. Think you’ve got what it takes?\nAbout the Role\nAt Advanced Space, we're enabling humanity's return to the Moon and building the technologies that will take us to Mars and beyond. We're looking for a Machine Learning Engineer with 5-8 years of experienceto develop innovative ML-driven capabilities that support spacecraft missions, autonomy, navigation, mission planning, and advanced engineering solutions.\nThis is a hands-on technical role focused on translating complex mission and engineering challenges into practical, data-driven solutions. You'll take ownership of technically complex projects from problem formulation and model development through quantitative evaluation, integration, and operational deployment. You'll work with modern machine learning techniques, including statistical learning, probabilistic modeling, optimization, deep learning, and reinforcement learning, to solve real-world aerospace challenges.\nWe're looking for someone who enjoys tackling ambiguous technical problems, has a strong foundation in machine learning and software engineering, and is excited to collaborate across disciplines to develop capabilities that support real space missions.\nThis position is open to U.S. Persons (U.S. citizens or lawful permanent residents) only. Visa sponsorship is not available.\nAbout Advanced Space\nAdvanced Space exists to enable the sustainable exploration, development, and settlement of space through innovative software, mission services, and technology solutions. As the owner and operator of NASA's CAPSTONE™ mission and the Prime Contractor for AFRL's Oracle mission, we're helping shape the future of cislunar exploration while supporting commercial, civil, and national security customers.\nOur team combines deep technical expertise with an entrepreneurial mindset. We move quickly, collaborate across disciplines, and empower every engineer to make meaningful contributions. If you're passionate about solving challenging problems and seeing your work fly in space, you'll fit right in.\nWhat You'll Actually Do\nDevelop machine learning solutions for complex engineering challenges.\nTranslate mission, operations, and engineering needs into well-defined ML and data-driven problems. Establish success metrics, baselines, datasets, evaluation plans, and quantitative acceptance criteria to develop solutions that address real-world mission requirements.\nDesign and implement ML-enabled capabilities.\nSelect, develop, evaluate, and maintain machine learning solutions that support spacecraft mission planning, operations, autonomy, navigation, physical-system modeling, signal extraction, and internal engineering workflows. Apply appropriate methods based on mission needs, data availability, computational constraints, and operational requirements.\nOwn technically complex projects from concept to deployment.\nTake ownership of technical work packages from initial problem formulation through implementation, integration, documentation, and operational handoff. Define technical approaches, assess trade-offs, identify risks, and communicate architectural decisions and recommendations to stakeholders.\nBuild reliable and reproducible ML workflows.\nDevelop and maintain end-to-end machine learning workflows, including data curation and validation, experiment tracking, model and data versioning, configuration management, automated regression testing, and performance monitoring. Apply modern software engineering practices to ensure solutions are maintainable, scalable, and reliable.\nEvaluate model performance and validate results.\nDesign rigorous evaluation strategies and domain-appropriate metrics to assess nominal, edge-case, and off-nominal performance. Identify data leakage, distribution shifts, and other factors that could impact model reliability. Use quantitative analysis and experimentation to validate model performance and inform technical decisions.\nIntegrate ML capabilities into aerospace systems.\nCollaborate with navigation, mission design, flight software, systems engineering, and operations teams to integrate machine learning solutions into broader engineering architectures and workflows. Ensure ML capabilities align with mission requirements, system constraints, and operational needs.\nResearch and apply emerging technologies.\nRead, synthesize, and apply relevant technical literature, emerging research, and innovative methodologies in machine learning, optimization, and autonomy. Evaluate new approaches and identify opportunities to advance Advanced Space's technical capabilities.\nCommunicate technical findings and recommendations.\nDocument technical approaches, assumptions, results, limitations, and recommendations. Present findings through design reviews, technical documentation, and stakeholder discussions, translating complex ML concepts into clear, actionable insights for multidisciplinary teams.\nLeverage modern AI-assisted engineering tools.\nUse company-approved AI-assisted and agentic engineering tools responsibly to support software development, documentation, research, and analysis. Critically evaluate generated outputs and apply appropriate security, source-provenance, reproducibility, and technical-validation practices.\nWho Thrives Here\nYou have a B.S. in Computer Science, Machine Learning, Software Engineering, Aerospace Engineering, or another relevant engineering, physical-science, or quantitative discipline. Equivalent relevant experience may be considered.\n\nYou have 5-8 years of professional experiencedeveloping and integrating machine learning, optimization, statistical, or data-driven engineering capabilities.\n\nYou have demonstrated experience owning technical problems from initial formulation through implementation, quantitative evaluation, documentation, and stakeholder communication.\n\nYou are proficient in Python and modern software engineering practices, including version control, code reviews, automated testing, debugging, and performance profiling.\n\nYou have experience with at least one modern ML framework, such as PyTorch, JAX, TensorFlow, or an equivalent, including developing custom models, loss functions, data pipelines, training loops, and inference workflows.\n\nYou understand common machine learning model families, including neural network architectures, and can select or adapt approaches based on data availability, computational constraints, mission requirements, and operational risk.\n\nYou have experience developing reproducible, end-to-end ML workflows, including data validation, experiment tracking, model and data versioning, integration testing, and model evaluation.\n\nYou have working knowledge of at least one aerospace domain, such as astrodynamics, spacecraft systems, navigation, mission design, or flight and ground software, or the ability to rapidly build expertise in these areas.\n\nYou are familiar with machine learning applications for physical or engineered systems, reinforcement learning, or decision-making methods.\n\nYou can effectively communicate complex technical concepts and collaborate with multidisciplinary engineering teams.\n\nYou take ownership of your work, approach challenges with curiosity, and are comfortable navigating technical ambiguity.\n\nBonus Points if You Have Experience With\nAn M.S. or Ph.D. in Aerospace Engineering, Computer Science, Artificial Intelligence, Robotics, or a related field.\n\nApplying model-based or model-free reinforcement learning, model predictive control (MPC), Markov decision processes (MDPs), partially observable Markov decision processes (POMDPs), or hybrid planning approaches to physical systems.\n\nDeveloping autonomy architectures spanning perception, estimation and navigation, planning and scheduling, control, and fault management.\n\nBuilding simulation or digital-twin environments for model development, evaluation, and sim-to-real transfer.\n\nIntegrating ML-enabled capabilities into guidance, navigation, and control (GN&C), mission design, navigation, flight software, or systems-engineering workflows.\n\nApplying optimization, probability, statistics, and rigorous experimental design to complex engineering problems.\n\nUsing probabilistic modeling or Bayesian inference to address engineering challenges.\n\nCommunicating complex technical concepts across machine learning, navigation, mission design, flight software, operations, and systems engineering.\n\nUsing agentic AI tools to support engineering workflows while maintaining technical accuracy, security, and reproducibility.\n\nSuccess is Measured By\nDelivering validated, reliable ML capabilities that address mission and engineering requirements.\n\nDeveloping and integrating machine learning solutions that support spacecraft autonomy, navigation, mission planning, and operations.\n\nBuilding reproducible ML workflows that improve model development, testing, evaluation, and deployment.\n\nDemonstrating measurable model performance through rigorous experimentation and quantitative evaluation.\n\nEffectively integrating ML capabilities into broader aerospace systems and engineering workflows.\n\nTaking ownership of complex technical challenges and delivering solutions from initial concept through implementation and operational handoff.\n\nCommunicating technical findings, limitations, risks, and recommendations clearly to engineering teams and stakeholders.\n\nContributing to the continued growth of Advanced Space's machine learning, autonomy, and engineering capabilities.\n\nWhy Join Advanced Space\nWork on real missions that are shaping the future of lunar and deep-space exploration.\n\nDevelop machine learning and autonomy solutions that support spacecraft operations and next-generation space technologies.\n\nCollaborate with experts in machine learning, navigation, mission design, and aerospace engineering.\n\nApply cutting-edge ML techniques to challenging, real-world engineering problems.\n\nBe part of a growing company where your technical contributions have a direct impact on mission success.\n\nJoin a team that's passionate about delivering innovation to orbit-and beyond.\n\nCompensation & Benefits\nBase Salary: $124K -$171K (based on experience, qualifications, and location)\n\nSigning bonus\n\nQuarterly performance bonuses\n\nCompany-sponsored medical benefits and 401(k)\n\nFlexible time off\n\nRelocation assistance\n\nAdvanced Space is an Equal Opportunity Employer.We celebrate diversity and are committed to creating an inclusive workplace for all employees. Employment decisions are made without regard to race, color, religion, sex, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.","description_format":"text","description_chars":10727,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Flexible time off","Relocation assistance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":true,"industries":["Space & Aerospace","Satellite Navigation","Space Services"],"lifecycle":[{"event":"open","at":"2026-10-03T05:34:39Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":3,"expected_fill_days":55,"reasons":["conf:1","win:early"],"computed_at":"2026-10-06T05:45:30Z"},"pay":{"stated_usd_annual":171000,"is_top_pay":false},"html_url":"https://alion.io/job/advancedspace-machine-learning-engineer-5-8-yrs","json_url":"https://alion.io/job/advancedspace-machine-learning-engineer-5-8-yrs.json","meta":{"generated_at":"2026-10-06T23:23:17Z","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","counted_by":"address","units_charged":1,"used_today":4744,"day_limit":5000,"remaining_today":256,"minute_limit":60,"resets_at":"2026-10-07T00:00:00Z"}},"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":7135},"rest":"https://alion.io/mcp/rest/get_company?id=7135"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fadvancedspace-machine-learning-engineer-5-8-yrs"},{"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%2Fadvancedspace-machine-learning-engineer-5-8-yrs"},{"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%2Fadvancedspace-machine-learning-engineer-5-8-yrs"},{"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/advancedspace-machine-learning-engineer-5-8-yrs\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fadvancedspace-machine-learning-engineer-5-8-yrs"}]}