Machine Learning Engineer (2-5 yrs)
Advanced Space12 hours ago
Westminster, CO, USAMid Level / Senior
Base Salary
$100k - $134k/yr
Responsibilities
- Translate mission, operations, and engineering needs into well-defined machine learning and data-driven problems with measurable success criteria.
- Design, implement, evaluate, and maintain ML solutions for spacecraft mission planning, operations, autonomy, navigation, physical-system modeling, signal extraction, and engineering workflows.
- Own technically complex work packages from initial formulation through implementation, integration, documentation, and operational handoff.
- Build reproducible end-to-end ML workflows covering data validation, experiment tracking, versioning, regression testing, and performance monitoring.
- Evaluate nominal, edge-case, and off-nominal model performance using rigorous quantitative analysis.
- Integrate ML capabilities with navigation, mission design, flight software, systems engineering, and operations teams.
- Research emerging machine learning, optimization, and autonomy methods and communicate technical findings, risks, limitations, and recommendations.
- Use approved AI-assisted and agentic engineering tools responsibly while maintaining security, source provenance, reproducibility, and technical validation.
Requirements
- Bachelor's degree in computer science, machine learning, software engineering, aerospace engineering, or another relevant engineering, physical-science, or quantitative discipline, with equivalent relevant experience considered.
- 2–5 years of professional experience developing and integrating machine learning, optimization, statistical, or data-driven engineering capabilities.
- Experience owning technical problems from formulation through implementation, quantitative evaluation, documentation, and stakeholder communication.
- Proficiency in Python and modern software engineering practices including version control, code reviews, automated testing, debugging, and performance profiling.
- Experience with at least one modern ML framework such as PyTorch, JAX, or TensorFlow, including custom models, loss functions, data pipelines, training loops, and inference workflows.
- Understanding of common machine learning model families and the ability to select methods based on data, computational constraints, mission requirements, and operational risk.
- Experience developing reproducible ML workflows with data validation, experiment tracking, model and data versioning, integration testing, and model evaluation.
- Working knowledge of an aerospace domain such as astrodynamics, spacecraft systems, navigation, mission design, or flight and ground software, or the ability to rapidly develop that expertise.
- Familiarity with machine learning applications for physical or engineered systems, reinforcement learning, or decision-making methods.
- Ability to communicate complex technical concepts and collaborate with multidisciplinary engineering teams.
- Preferred experience includes a relevant master's degree, reinforcement learning, model predictive control, Markov decision processes, POMDPs, autonomy architectures, simulation or digital-twin environments, GN&C integration, probabilistic modeling, Bayesian inference, and agentic AI tools.
Benefits
- Hybrid, full-time position.
- Base salary of $100K–$134K based on experience, qualifications, and location.
- Signing bonus and quarterly performance bonuses.
- Company-sponsored medical benefits and 401(k).
- Flexible time off.
- Relocation assistance.
- Work on real lunar and deep-space missions and collaborate with machine learning, navigation, mission design, and aerospace experts.
Categories
About Advanced Space
Advanced Space provides mission design, navigation, flight dynamics software, and mission systems engineering to commercial, civil, and national security space programs. The privately held company, founded in 2011 and headquartered in Westminster, Colorado, also delivers turnkey missions and autonomy/AI technology, operating NASA’s CAPSTONE lunar mission and serving as prime contractor for AFRL’s Oracle cislunar situational awareness effort. Revenue comes from government contracts and commercial services, spanning lunar to deep-space applications.