Machine Learning Engineer designing and implementing AI systems focused on Japanese language challenges at Woven by Toyota. Involves technical R&D, system design, and collaboration with cross - functional teams.
About the role
- Senior ML Platform Engineer building and scaling machine learning infrastructure for AI applications. Responsible for LLM deployment, Kubernetes management, and mentoring engineering teams.
Responsibilities
- Build and scale machine learning infrastructure focused on Large Language Models (LLMs) and AI applications
- Design and implement scalable infrastructure for training, fine-tuning, and serving open source LLMs
- Architect and manage Kubernetes clusters for ML workloads
- Ensure 99.9%+ uptime for ML platforms through robust monitoring
- Mentor junior engineers and data scientists on platform best practices
- Collaborate with data scientists and product engineering teams
- Present technical solutions and platform roadmaps to leadership
Requirements
- Bachelor’s degree in computer science, Engineering, or related technical field (or equivalent experience)
- 5+ years of software engineering experience with focus on infrastructure, platform engineering, or MLOps
- 2+ years of hands-on experience with machine learning infrastructure and deployment at scale
- 1+ years of experience working with Large Language Models and transformer architectures
- Proficient in Python; strong skills in Go, Rust, or Java preferred
- Proven experience working with open source LLMs (Llama 2/3, Qwen, Mistral, Gemma, Code Llama, etc.)
- Proficient in Kubernetes including custom operators, helm charts, and GPU scheduling
- Deep expertise in Azure services (AKS, Azure ML, Container Registry, Storage, Networking)
Benefits
- Comprehensive Total Rewards program that offers personalized coverage
- Health insurance
- 401(k) savings plan vested from day one that offers a 6% match
- Performance and recognition-based incentives
- Tuition assistance
- Workplace flexibility as well as GEICO Flex program allowing work from anywhere in the US for up to four weeks per year
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