Senior AI/ML Engineer, Navigation Algorithms
Washington, Utah, United States of America
Contract
1 day ago
Key skills
PythonC++CGoAIMachine LearningML
About this role
Job Title: Senior AI/ML Engineer, Navigation Algorithms
Location: Washington, DC
Duration: Full-time (Direct Hire)
Schedule: Hybrid Role
Job Description:
About the Role:
As a Senior AI/ML Engineer, you will work on navigation-related algorithms that support fast reasoning through complex environments. You should be comfortable developing algorithms, building evaluation methods, analyzing performance tradeoffs, and supporting the data and inference pipelines needed to bring those capabilities into production.
This role is ideal for an engineer with strong Python experience, strong algorithmic instincts, and comfort working in technical domains involving spatial data, simulation, or complex environments. Experience with lower-level or object-oriented languages such as C++ or Go is a plus.
Responsibilities:
- Develop, train, test, and evaluate navigation, spatial reasoning, and path-planning algorithms.
- Build algorithms that support fast movement, routing, or reasoning through complex 3D environments.
- Build and maintain data pipelines and inference pipelines for navigation-related capabilities.
- Define metrics and evaluation methods for each model, algorithm, or pipeline delivered.
- Analyze accuracy, latency, robustness, scalability, and operational limitations.
- Collaborate with backend, data, product, and AI/ML teams to integrate capabilities into the broader platform.
- Document algorithm behavior, evaluation results, limitations, and operational considerations.
Required Qualifications:
- 5+ years of professional software engineering, machine learning, data science, algorithm development, or applied AI experience.
- Strong proficiency in Python and modern engineering or machine learning workflows.
- Experience with navigation, routing, path planning, spatial reasoning, simulation, robotics, geospatial systems, 3D environments, or related domains.
- Experience training, testing, evaluating, and benchmarking algorithms or machine learning models.
- Experience building data pipelines, inference pipelines, or production algorithm workflows.
- Ability to define clear metrics for performance, accuracy, latency, robustness, and reliability.
- Strong understanding of data structures, algorithms, optimization, and production AI/ML practices.