Machine Learning Engineer designing and deploying advanced training capabilities to support U.S. Navy operational readiness. Collaborate on machine - learning models to enhance combat system training environments.
About the role
- Lead ML Ops Engineer for a fast-growing AI startup focused on scalable infrastructure. Drive hands-on execution across the entire model lifecycle in a collaborative environment.
Responsibilities
- Architect, build, and scale the end-to-end ML Ops pipeline, including training, fine-tuning, evaluation, rollout, and monitoring.
- Design reliable infrastructure for model deployment, versioning, reproducibility, and orchestration across cloud and on-prem GPU clusters.
- Optimize compute usage across distributed systems (Kubernetes, autoscaling, caching, GPU allocation, checkpointing workflows).
- Lead the implementation of observability for ML systems (monitor drift, performance, throughput, reliability, cost).
- Build automated workflows for dataset curation, labeling, feature pipelines, evaluation, and CI/CD for ML models.
- Collaborate with researchers to productionize models and accelerate training/inference pipelines.
- Establish ML Ops best practices, internal standards, and cross-team tooling.
- Mentor engineers and influence architectural direction across the entire AI platform.
Requirements
- Deep hands-on experience designing and operating production ML systems at scale (Staff/Principal-level expected).
- Strong background in ML Ops, distributed systems, and cloud infrastructure (AWS, GCP, or Azure).
- Proficiency with Python and familiarity with TypeScript or Go for platform integration.
- Expertise in ML frameworks: PyTorch, Transformers, vLLM, Llama-factory, Megatron-LM, CUDA / GPU acceleration (practical understanding)
- Strong experience with containerization and orchestration (Docker, Kubernetes, Helm, autoscaling).
- Deep understanding of ML lifecycle workflows: training, fine-tuning, evaluation, inference, model registries.
- Ability to lead technical strategy, collaborate cross-functionally, and operate in fast-paced environments
Benefits
- Competitive salary & equity options
- Sign-on bonus
- Health, Dental, and Vision
- 401k
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
Location requirements
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