Ml Engineer Jobs

About The Position

Requirements

• Advanced degree (Master’s or PhD) in Computer Science, Artificial Intelligence, or a related STEM field
• 8+ years of experience in AI/ML engineering, software engineering, or related field
• Strong background in building and deploying machine learning models in production environments
• Experience designing and maintaining ML pipelines and platforms including training, inference, and monitoring
• Proficiency in Python and modern ML frameworks such as PyTorch, TensorFlow, or Scikit-learn
• Strong software engineering fundamentals including APIs, microservices, testing, and version control
• Experience working in cloud-native environments such as AWS, Kubernetes, and containerization
• Ability to lead technical initiatives and collaborate across interdisciplinary teams
• Track record of setting multi-year technical strategy and delivering AI/ML capabilities that directly drove revenue growth, customer acquisition, or measurable mission impact
• Experience establishing AI governance, model risk management, and responsible AI practices at an enterprise scale
• Minimum Secret security clearance with ability to obtain and maintain an active TS SCI clearance

Nice To Haves

• Experience with LLMs, RAG architectures, and agent-based systems
• Experience deploying AI systems in edge, air-gapped, or secure environments
• Familiarity with event-driven and data streaming architectures such as Kafka
• Experience with MLOps tooling and workflows including CI/CD for ML, model versioning, and observability
• Contributions to open-source projects, publications, or a strong GitHub portfolio
• Experience with TypeScript or full-stack integration of AI systems

Responsibilities

• Lead the architecture and development of AI/ML systems integrated into production-grade data platforms
• Design and implement scalable ML pipelines including training, inference, and evaluation in distributed environments
• Drive adoption of modern AI approaches including LLMs, retrieval augmented generation, and agentic workflows
• Design, train, fine-tune, and deploy purpose-built Small Language Models (SLMs) optimized for domain-specific tasks, including quantization, distillation, and optimization techniques that enable low-latency inference in resource-constrained, edge, and air-gapped environments
• Partner with Data Engineers and DevSecOps to operationalize models in secure, containerized environments including Kubernetes and CI/CD pipelines
• Translate mission needs into technical solutions while working directly with customers and stakeholders
• Mentor and guide engineers while setting technical direction and best practices for AI/ML development
• Ensure models are reliable, observable, and performant in real-world operational conditions
• Own the enterprise-wide AI/ML strategy and multi-year technical roadmap, aligning research, engineering, and product investments with mission outcomes and commercial objectives
• Build, scale, and lead a multi-team AI/ML organization, including hiring, performance management, and developing senior technical leaders across applied research, ML engineering, and MLOps
• Establish and steward the technical vision for agentic systems, foundation models, and emerging AI paradigms, identifying strategic bets and guiding applied research investments that create long-term competitive advantage

Benefits

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Generous Referral Bonuses
• And More!