Senior Machine Learning (ML) Engineer

ABOUT THE TEAM

Andurils Air & Missile Defense Radar team develops cutting-edge tracking algorithms and software systems that detect track and characterize airborne threats in real-time. Were building the next generation of tracking intelligence capabilitiesautomated analysis systems that understand tracking performance identify failure modes and continuously improve our algorithms through data-driven insights.

This role sits at the intersection of ML engineering and tracking domain expertise. Youll build end-to-end pipelines that ingest tracking algorithm telemetry analyze correlation failures and performance anomalies train models to automate root cause analysis and deploy production tools that help engineers ask questions like why didnt track X and track Y associate We dont just track targets; we track our tracking systems and make them smarter.

WHAT YOULL DO

• 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 anomaliesreplacing 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 validationensuring 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 initiallyyoull architect code deploy and iterate rapidly using modern Python-based ML tooling

REQUIRED QUALIFICATIONS

• 3 years of experience with a strong mix of ML engineering and data scienceyouve 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 fundamentalsyou 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

PREFERRED QUALIFICATIONS

• 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

The salary range for this role is an estimate based on a wide range of compensation factors inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience education and/or training critical skills and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Andurils total compensation package. Additionally Anduril offers top-tier benefits for full-time employees including:

Healthcare Benefits

• US Roles:Comprehensive medical dental and vision plans at little to no cost to you.
• UK & AUS Roles:We cover full cost of medical insurance premiums for you and your dependents.
• IE Roles: We offer an annual contribution toward your private health insurance for you and your dependents.

Additional Benefits

• 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.

Retirement Savings Plan

• US Roles:Traditional 401(k) Roth and after-tax (mega backdoor Roth) options.
• UK & IE Roles:Pension plan with employer match.
• AUS Roles:Superannuation plan.

The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.

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