Machine Learning/MLOps Engineer at Anduril Industries

Costa Mesa, California, United States -

Full Time

Start Date

Immediate

Expiry Date

03 Mar, 26

Salary

253000.0

Posted On

03 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning Engineering, MLOps, Backend Workflow Automation, Python, ML Frameworks, Data Processing Libraries, Containerized Services, MLOps Practices, APIs, Problem-Solving Skills, Workflow Automation, Event-Driven Architectures, Integration with Enterprise Systems, Observability Systems, Human-in-the-Loop Workflows, Workflow Orchestration Tools

Industry

Defense and Space Manufacturing

Description

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years. ABOUT THE TEAM Anduril Maritime delivers platforms, systems, and integrated effects in the maritime domain. Our autonomous vehicles (sub-surface and surface) are the cornerstone of these capabilities, and we continually strive to push the boundaries of the possible in terms of endurance, autonomy and mission capability. The Maritime team develops and maintains core products and payloads, and adapts and applies those products to serve a wide variety of defense, IC and commercial customers in US and international markets. ABOUT THE JOB We are seeking a Machine Learning/MLOps Engineer to join the Applied Intelligence team within Maritime Digital Production. You will help build the applied AI and automation systems that streamline business processes and shipyard workflows across design, production, logistics, and quality. This role focuses on operationalizing models, automating manual workflows, and developing the infrastructure that enables AI-driven decision support across the Build Chain. You’ll work across software, data, and operational technology domains to develop pipelines, model-serving components, orchestration logic, and monitoring tools that keep AI-enabled workflows reliable, auditable, and safe. You will translate real user pain points into automated digital workflows—applying AI only where it adds value and leaning on simpler automation when it doesn’t. Your work will improve throughput, reduce administrative burden, and accelerate decision velocity across the broader Maritime Digital ecosystem. WHAT YOU’LL DO Develop and maintain data pipelines, feature engineering workflows, and model-serving components that support applied AI use cases across the yard. Implement automation workflows that streamline business and production processes—applying models, logic, and orchestration to remove manual steps and reduce friction. Integrate off-the-shelf models (OCR/IDP, CV, RAG, STT) into workflow solutions using standardized APIs, datasets, and orchestration layers. Build and maintain MLOps pipelines for data ingestion, labeling, versioning, training, evaluation, deployment, monitoring, and rollback. Deploy workflow automation and model-serving components in event-driven environments integrated with PLM, MES, CMMS, ERP, and unified data layers. Contribute to observability tools for monitoring inference performance, data quality, and workflow reliability. Collaborate with digital, manufacturing, and corporate technology teams to map current workflows, identify automation opportunities, and integrate solutions safely. Ensure all deployed AI/automation workflows include human-in-the-loop gates, audit trails, and compliance features required for production operations. Document integration contracts, workflow logic, data flows, and operational runbooks to support scaling and handoff. REQUIRED QUALIFICATIONS Strong stakeholder and cross-functional communication skills; able to gather workflow requirements and convert them into technical automation. 3–6 years of experience in machine learning engineering, MLOps, or backend workflow automation. Proficiency in Python and experience with ML frameworks (PyTorch or TensorFlow) and data processing libraries. Experience building and deploying containerized services (Docker; familiarity with Kubernetes preferred). Understanding of MLOps practices: data pipelines, model versioning, evaluation, CI/CD for ML, monitoring, and retraining. Experience working with off-the-shelf models (OCR/IDP, CV, STT, RAG) and integrating them into workflow pipelines. Familiarity with event-driven architectures, IoT or UNS patterns, and integration with enterprise systems. Experience with APIs, schema-based integration, and data contracts. Strong problem-solving skills with an ability to simplify workflows into modular, reusable automation components. Eligible to obtain and maintain an active U.S. Secret security clearance. PREFERRED QUALIFICATIONS Experience automating workflows in manufacturing, logistics, or enterprise business processes. Experience with workflow orchestration tools (Airflow, Flyte, Prefect, Temporal). Familiarity with data engineering concepts, time-series data, and semantic/ontology-driven data structures. Exposure to observability systems (Prometheus, Grafana, ELK) for monitoring workflow reliability or model performance. Experience integrating AI models with PLM, MES, ERP, CMMS, or similar industrial systems. Interest in developing adaptive, human-in-the-loop workflow automations that blend ML, rules, and operational context. US Salary Range $191,000—$253,000 USD 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 Anduril's 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. To view Anduril's candidate data privacy policy, please visit https://anduril.com/applicant-privacy-notice/.

Responsibilities

Develop and maintain data pipelines and model-serving components to support applied AI use cases. Implement automation workflows to streamline business and production processes, ensuring reliability and compliance.