Senior Machine Learning/MLOps Engineer

Anduril Industries

Quick summary

Work type
On-site
Location
Costa Mesa, CA
Salary
$220,000–$292,000 / yr
Posted
today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $214k
This role $256k
$148k most similar roles pay here $307k

This role pays more than 76% of similar roles. Most pay $175,875–$252,625 — the shaded band above. At the midpoint, this role pays about $256k versus about $214k for comparable roles.

Based on 240 similar postings.

Employer

About Anduril Industries

Anduril Industries is a defense technology company that builds advanced hardware and software systems for national security, including autonomous drones, surveillance systems, and the Lattice AI command platform.

Anduril Industries currently has 1882 open roles on FindRole.

Listed pay typically runs $146,000–$194,000 across 1696 roles with salary data.

Most-posted roles

View all roles at Anduril Industries

At a glance

TL;DR · Senior Machine Learning/MLOps Engineer

As a Senior Machine Learning/MLOps Engineer on the Applied Intelligence team within Maritime Digital Production, you will lead the design and deployment of an AI-enabled backbone for digital shipbuilding. Your responsibilities include architecting and implementing core components such as data stores, vector databases, and model-serving frameworks, while integrating off-the-shelf models for computer vision, OCR/IDP, speech, and retrieval-augmented generation. You’ll work across various teams to translate real factory scenarios into applied AI capabilities with human-in-the-loop controls and integrations with enterprise systems like PLM, MES, CMMS, and ERP. The role requires expertise in Python, deep learning frameworks (PyTorch, TensorFlow), Docker, Kubernetes, and data engineering, along with experience in MLOps practices and observability for model performance. Ideal candidates have a background in manufacturing or logistics environments and can mentor junior engineers while setting technical direction for AI/ML infrastructure at scale.

What you'll do

  • Architect and own the AI/ML platform stack from data ingestion to model lifecycle management.
  • Select and standardize industrial AI components like feature stores, vector databases, and orchestration layers.
  • Build optimized model-serving frameworks for real-time and batch execution across various environments.
  • Translate factory scenarios into applied AI workflows with human-in-the-loop controls and integrations.
  • Implement event-driven data pipelines to feed models with contextualized signals from production systems.
  • Lead reliability engineering by managing drift detection, retraining triggers, alerting, and operational SLOs.

What we're looking for

  • 8+ years of experience in software or ML engineering with end-to-end delivery of production-grade AI/ML systems.
  • Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow).
  • Deep MLOps expertise including data acquisition, labeling, pipeline management, model versioning, CI/CD, and monitoring.
  • Experience building and deploying containerized ML services using Docker and Kubernetes.
  • Proficiency in data engineering, time-series modeling, and semantic/ontology-driven systems.
  • Familiarity with event-driven architectures, IoT patterns, and real-time system integration.
  • Excellent communication skills to bridge research, platform, and production domains.

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