Senior Machine Learning (ML) Engineer

Anduril Industries • Fort Collins, CO

7h

About The Position

Anduril Industries is a defense technology company focused on transforming military capabilities with advanced technology. The Air & Missile Defense Radar team specifically develops cutting-edge tracking algorithms and software systems to detect, track, and characterize airborne threats in real-time. This role is at the intersection of ML engineering and tracking domain expertise, focusing on building end-to-end pipelines for ingesting tracking algorithm telemetry, analyzing performance, training models for root cause analysis, and deploying production tools to help engineers understand tracking behavior. The goal is to make tracking systems smarter by analyzing their performance.

This role involves building the platform for ingesting tracking algorithm telemetry, engineering performance metrics, training analysis models, and deploying them into production. It also includes automating tracking analysis through ML models to identify correlation failures and track quality degradation, building systems for autotuning tracking algorithms based on data characteristics, and designing tools for engineers to query tracking behavior. The role requires instrumenting C++ tracking algorithms for telemetry logging, marshaling data for analysis, and deploying models in constrained, air-gapped environments. Managing the ML lifecycle, including data catalogs, ground truth labeling, model registries, versioning, and validation, is also key. The engineer will translate between tracking algorithm fundamentals and ML techniques, drive make/build decisions for ML solutions, and work hands-on with modern Python-based ML tooling.

Requirements

• 3+ years of experience with a strong mix of ML engineering and data science—you've built models AND deployed them into production systems
• Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, scikit-learn)
• Experience with MLOps practices: data pipelines, feature engineering, model versioning, experiment tracking, and deployment workflows
• Familiarity with ML infrastructure tooling (MLflow, Dagster/Airflow, or similar orchestration tools)
• Understanding of tracking, estimation, or filtering algorithms (Kalman filters, data association techniques)—you need to understand what tracking algorithms output and why they make the decisions they do
• Ability to work with streaming time-series data and engineer features from algorithm telemetry
• Experience building data catalogs, managing ground truth labels, and validating model performance
• Strong software engineering fundamentals—you can build maintainable, production-quality code independently
• Comfortable working in C++ environments enough to add instrumentation/logging (no deep algorithm development required)
• Ability to obtain and maintain a U.S. Top Secret SCI security clearance

Nice To Haves

• Experience deploying ML models in edge, embedded, or air-gapped environments with security constraints
• Background in defense, aerospace, or sensor systems
• Familiarity with containerization (Docker, Kubernetes) for model serving and deployment
• Experience with anomaly detection, root cause analysis, or automated diagnostics systems
• Knowledge of AutoML, hyperparameter tuning, or online learning techniques
• Understanding of radar systems, sensor fusion, or signal processing
• Experience building conversational or query interfaces for technical systems
• Familiarity with model registries and model-as-data artifact management
• Experience with distributed data processing (Spark, Dask) for large-scale telemetry analysis
• Formal coursework or training in MLOps, data science, or estimation theory
• Active U.S. Top Secret SCI clearance

Responsibilities

• Own tracking intelligence infrastructure end-to-end: Build the platform for ingesting tracking algorithm telemetry (hypotheses, scores, gains, association decisions), feature engineering performance metrics, training analysis models, and deploying them into production
• Automate tracking analysis: Develop ML models that identify correlation failures, track quality degradation, and root causes for tracking anomalies—replacing manual deep-dive investigations with scalable automated insights
• Build autotuning capabilities: Create systems that recognize incoming data characteristics and automatically adjust tracking algorithm parameters, frame rates, and model configurations for optimal performance
• Design human-in-the-loop tools: Build interfaces and query services that let engineers ask natural questions about tracking behavior and get data-driven answers backed by your models
• Exploit tracking telemetry: Instrument C++ tracking algorithms with appropriate logging (working with platform engineers), then marshal that data into consistent formats for analysis and model training
• Deploy in constrained environments: Package and deploy models for air-gapped systems with no external connectivity, following security scanning requirements where ML models are treated as data artifacts
• Manage the ML lifecycle: Handle data catalogs, ground truth labeling, model registries, versioning, and validation—ensuring models improve tracking performance in measurable ways
• Bridge domains: Translate between tracking algorithm fundamentals (Kalman filters, data association, multi-hypothesis tracking) and ML/data science techniques to build solutions that actually work
• Drive make/build decisions: Evaluate when to build custom models vs. leverage existing ML capabilities, selecting appropriate algorithm architectures for tracking intelligence problems
• Work hands-on-keyboard: This is a one-person show initially—you'll architect, code, deploy, and iterate rapidly using modern Python-based ML tooling

Benefits

• Comprehensive medical, dental, and vision plans at little to no cost to you.
• Income Protection: Anduril covers life and disability insurance for all employees.
• Generous time off: Highly competitive PTO plans with a holiday hiatus in December. Caregiver & Wellness Leave is available to care for family members, bond with a new baby, or address your own medical needs.
• Family Planning & Parenting Support: Coverage for fertility treatments (e.g., IVF, preservation), adoption, and gestational carriers, along with resources to support you and your partner from planning to parenting.
• Mental Health Resources: Access free mental health resources 24/7, including therapy and life coaching. Additional work-life services, such as legal and financial support, are also available.
• Professional Development: Annual reimbursement for professional development
• Commuter Benefits: Company-funded commuter benefits based on your region.
• Relocation Assistance: Available depending on role eligibility.
• Traditional 401(k), Roth, and after-tax (mega backdoor Roth) options.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed