Software Engineer - Machine Learning

Garmin International, Inc.•Boulder, CO

About The Position

Garmin is seeking a full-time Senior Software Engineer in the Greater Denver area to build platforms, tooling, and infrastructure for scalable delivery of machine learning and large language model (LLM) capabilities. The role partners with Data Scientists, Software Engineers, and Cloud/Infrastructure teams to develop self-service ML Ops solutions that reduce friction in model deployment, monitoring, reliability, and operational support. The engineer will help shape AI enablement at Garmin by designing production-grade systems that improve the scalability, efficiency, and developer experience of enterprise AI/ML workflows. The role also includes senior individual-contributor software development and may include leading complex software projects, reviewing system designs, mentoring less experienced engineers, providing technical assessments, and contributing to project planning and technical research. Rotating on-call hours support Garmin’s 24/7 operations.

Requirements

Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, Software Engineering, Aerospace Engineering, Math, Physics, or a related field, plus at least 5 years of relevant experience; or an equivalent combination of education and experience.
Cumulative GPA of at least 3.0 as a general rule.
Proficiency designing well-architected software systems and modules that support new technology or improve existing capability or performance.
Competence researching fundamental problems and implementing appropriate algorithmic solutions.
Ability to serve as lead software engineer for a complex software project.
Ability to decompose functional requirements into well-defined tasks while balancing quality, quantity, and complexity.
Ability to provide peer technical assessments in areas of expertise, new technologies, and software designs.
Mastered proficiency writing software in C, C++, C#, or Java, with relevant experience or training in data structures or object-oriented design methodology.
Strong verbal, written, and interpersonal communication skills.
Positive, detail-oriented, organized, and team-oriented approach; driven problem solver, multitasker, and self-starter able to prioritize and lead in a fast-paced, deadline-driven environment.

Nice To Haves

Cumulative GPA of at least 3.5.
Experience developing and supporting containerized and distributed systems using technologies such as Docker, Kubernetes, Helm, and cloud-native deployment platforms.
Familiarity with GPU-enabled infrastructure, accelerated compute environments, and scalable inference architectures for machine learning and LLM workloads.
Experience with cloud compute and storage platforms such as Microsoft, including deployment automation, networking, and infrastructure management.
Knowledge of ML Ops and DevOps tooling, including CI/CD pipelines, infrastructure-as-code, model deployment workflows, observability platforms, and operational monitoring solutions.
Familiarity with modern machine learning frameworks, model-serving technologies, and artifact management solutions such as PyTorch, Hugging Face, and MLflow.
Experience developing automation and self-service tooling using Python, REST APIs, scripting frameworks, and cloud-based orchestration technologies.

Responsibilities

Design, develop, and maintain self-service Machine Learning Operations tooling, platforms, and automation for efficient, scalable model delivery.
Implement and support standardized CI/CD pipelines, model registries, deployment automation, and operational tooling for production AI/ML systems.
Collaborate with Data Scientists, Software Engineers, and Infrastructure teams to improve model development and deployment workflows and developer experience.
Design and implement monitoring, health checks, observability, and alerting for production machine learning and LLM deployments.
Research and implement scalable infrastructure for LLM deployment, including autoscaling, dynamic routing, and cloud-based serving architectures.
Develop software in Python, Java, or other selected languages for new products and applications.
Lead complex software development projects and review architectures, modules, and systems that support new technology or improve existing functionality.
Decompose functional requirements into well-defined tasks.
Research fundamental problems and implement appropriate algorithmic solutions.
Provide peer technical assessments on areas of expertise, new technologies, and software designs.
Assist design engineering with component datasheet and schematic design reviews as needed.
Participate in project leadership and program planning, providing technical input to product development plans and concept documents.
Contribute to project goal and objective feasibility decisions and use sound judgment in setting schedules and taking risks.
Mentor and guide less experienced Software Engineers (levels 1 and 2).
Contribute to advanced technical research on new technologies.
Suggest process improvements and author procedures as appropriate.
Provide reliable solutions to difficult problems using sound problem-solving techniques.
Support rotating on-call hours for Garmin’s 24/7 operations.