Staff Applied Machine Learning Engineer

Job Title

Staff Applied Machine Learning Engineer

Location: San Francisco or Washington DC area (hybrid)

Rest of US: open to relocating (support offered)

Intro

A specialist technology business at the forefront of intelligent systems is seeking an experienced staff-level applied machine learning engineer to help shape the next generation of edge-deployed AI. This is a hands-on role for someone who enjoys solving complex, real-world problems and seeing their work operate in demanding, mission-critical environments.

The Opportunity

This role sits at the intersection of research and production, offering the chance to shape both the technical roadmap and the way machine learning is applied across complex perception challenges. The successful candidate will take ownership of key initiatives, guide architectural decisions, and support the growth of other experienced engineers, while remaining close to the technology.

Working within a cross-functional team spanning hardware, software and product, they will help deliver robust, efficient AI systems designed to operate reliably in constrained, edge-based environments. There is clear scope for progression into formal leadership or management for those interested.

Key Responsibilities

• Lead the design, development and deployment of machine learning models across tasks such as object detection, classification, anomaly detection and sensor-based inference
• Own end-to-end ML initiatives, from problem definition and experimentation through to production deployment
• Provide technical leadership on model architecture, system design and edge deployment strategies
• Optimise models and inference pipelines for embedded hardware under strict compute and bandwidth constraints
• Shape dataset strategy, including labelling, augmentation, synthetic data generation and domain adaptation
• Guide experimentation across computer vision, signal processing and multi-modal fusion
• Mentor and support experienced engineers, contributing to their technical development and best practices
• Build and refine real-time processing pipelines across on-device and cloud environments
• Develop internal tools for benchmarking, debugging and performance analysis
• Evaluate emerging research and technologies, influencing their adoption within the product roadmap
• Contribute to code quality, technical standards and knowledge sharing across the team

What They’re Looking For

• Strong academic background in Machine Learning, Computer Vision, Robotics or a related field (Master’s or PhD preferred)
• Significant experience (typically 10+ years) building and deploying ML models in production
• Deep expertise in Python and modern ML frameworks such as PyTorch or TensorFlow
• Proven track record working with diverse data types (e.g. image, time-series, geospatial or RF data)
• Strong experience deploying and optimising models for edge or embedded systems
• Solid grounding in ML best practices, including validation, tuning and monitoring at scale
• Ability to lead projects, influence technical direction and make pragmatic engineering decisions
• Experience mentoring or guiding other engineers
• Strong communication skills, able to engage effectively with both technical and non-technical stakeholders
• Eligibility to obtain and maintain security clearance
• Background in maritime, aerospace or remote sensing domains would be advantageous

Important to know

Unfortunately, due to the sector the company operates in, they can only consider US Citizens eligible for Security Clearance for this role.