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Anduril Industries · 12 hours ago

Senior Machine Learning/MLOps Engineer

Costa Mesa, CA

Full-time

Onsite

Senior Level, Lead/Staff

$220K/yr - $292K/yr

8+ years exp

Anduril Industries is a defense technology company focused on transforming military capabilities with advanced technology. The Senior Machine Learning/MLOps Engineer will lead the design and deployment of AI-enabled systems in the maritime domain, operationalizing advanced models and architecting the industrial AI stack to enhance production and logistics.

AerospaceArtificial Intelligence (AI)GovernmentMilitaryNational Security

No H1B

Security Clearance Required

U.S. Citizen Only

Responsibilities

Architect and own the AI/ML platform stack—from data ingestion, labeling, and feature engineering to model training, deployment, monitoring, and lifecycle management

Select, prioritize, and standardize industrial AI components including feature stores, vector databases + RAG, OCR/IDP and CV/STT providers, orchestration layers, and observability systems

Build model-serving and inference frameworks optimized for production environments, supporting real-time and batch execution across cloud, edge, and shop-floor systems

Translate factory scenarios (receiving, inspection, RCCA, scheduling) into applied AI workflows with defined human-in-the-loop gates, audit trails, and integration contracts with PLM, MES, CMMS, ERP, and the unified data plane

Implement event-driven data pipelines and telemetry systems that feed models with contextualized, real-time signals from production and logistics systems

Drive make/buy strategy by researching internal and vendor AI capabilities and recommending investments aligned to enterprise roadmaps, Anduril IP principles, and production constraints

Define and maintain model governance processes for validation, safety reviews, traceability, and rollback

Partner with Maritime platform teams and CorpTech to align architectures with enterprise data standards, ontologies, and compliance policies

Lead reliability engineering for deployed models—managing drift detection, retraining triggers, alerting, and operational SLOs

Mentor junior engineers and data scientists; establish best practices for MLOps, observability, data management, and secure handling of sensitive production data

Qualification

MLOpsPythonDeep learning frameworksContainerization DockerContainerization KubernetesData engineeringModel governanceEvent-driven architecturesStakeholder managementCommunication skillsMentoringDocumentation abilities

Required

Strong stakeholder management skills with proven experience aligning engineering, data, and manufacturing teams

8+ years of experience in software or ML engineering with end-to-end delivery of production-grade AI/ML systems

Deep experience with MLOps: data acquisition, labeling, curation, pipeline management, model versioning, continuous integration, and model monitoring

Strong proficiency in Python and experience with deep learning frameworks (PyTorch, TensorFlow)

Experience building and deploying containerized ML services using Docker and Kubernetes

Proficiency in data engineering, time-series data modeling, and working with semantic/ontology-driven data systems

Experience implementing observability for model performance, inference accuracy, and data drift

Familiarity with event-driven architectures, IoT/UNS patterns, and real-time systems integration

Excellent communication and documentation abilities; able to bridge research, platform, and production domains

Eligible to obtain and maintain an active U.S. Secret security clearance

Preferred

Experience applying AI/ML within manufacturing, logistics, industrial control, or production environments

Background with digital twins, predictive maintenance, OCR/IDP, CV, or STT model integrations

Experience with workflow/orchestration tools such as Flyte, Airflow, Kubeflow, or Temporal

Familiarity with GPU acceleration (CUDA) and inference optimization (TensorRT, Triton)

Experience in regulated environments (NNPI/ITAR) and secure model/data governance

Demonstrated ability to mentor engineers and set technical direction for AI/ML infrastructure at scale

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.

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.