Software Engineer - Machine Learning

Garmin International, Inc.•Olathe, KS

20h

About The Position

Garmin is seeking a full-time Software Engineer at its U.S. headquarters in the Greater Kansas City area. The role builds platforms, tooling, and infrastructure that enable scalable delivery of machine learning and large language model (LLM) capabilities across Garmin. The engineer 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 position designs production-grade systems to improve the scalability, efficiency, and developer experience of enterprise AI/ML workflows. It includes software development and technical leadership as an individual contributor, with possible lead responsibilities on complex projects. The engineer also supports Garmin’s 24/7 operations through on-call work as part of a rotating schedule.

Requirements

Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, Software Engineering, Aerospace Engineering, Math, Physics, or a related field, and a minimum of 2 years of relevant experience.
Demonstrated proficiency designing well-architected software systems and modules that support new technology or improve the capability or performance of existing functionality.
Demonstrated competence researching fundamental problems and implementing appropriate algorithmic solutions.
Demonstrated ability to serve as a lead software engineer for a complex software project.
Ability to decompose functional requirements into well-defined tasks while balancing quality, quantity, and complexity in work output.
Demonstrated capability to offer peer technical assessments in areas of expertise, new technologies, and software designs.
Mastered proficiency writing software in C, C++, C#, or Java, and relevant experience and/or training in data structures or object-oriented design methodology.
Strong and effective verbal, written, and interpersonal communication skills.
Positive, detail-oriented, organized, team-oriented, and driven problem solver, multitasker, and self-starter, with the ability to prioritize and lead in a fast-paced, deadline-driven environment.

Nice To Haves

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 supporting machine learning and LLM workloads.
Experience working 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, MLflow, or similar technologies.
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 Ops tooling, platforms, and automation capabilities to improve the efficiency and scalability of machine learning 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 reduce operational friction and improve the developer experience for model development and deployment workflows.
Design and implement monitoring, health check, observability, and alerting capabilities for production machine learning and LLM deployments.
Research and implement scalable infrastructure solutions for LLM deployment, including autoscaling, dynamic routing, and cloud-based serving architectures.
Carry out software development in Python, Java, or other selected languages for new products and applications.
May lead complex software development project designs and/or review architected modules and software systems supporting new technology or improving existing functionality.
Decompose functional requirements into well-defined tasks.
Research fundamental problems and implement appropriate algorithm solutions.
Offer peer technical assessments in areas of expertise, new technologies, and software designs.
Participate in project leadership and/or program planning, including providing technical input to product development plans and concept documents.
Contribute to determining project goal and objective feasibility and apply judgment in setting schedules and taking risks.
Mentor and provide guidance to less experienced Software Engineers (1 & 2).
Contribute to advanced technical research on new technologies.
Offer process improvement suggestions and author new procedures as appropriate.
Provide reliable solutions to a wide range of difficult problems using sound problem-solving techniques.
Support working hours as part of a rotating schedule to provide on-call support for Garmin’s 24/7 operations.