Senior ML Platform Engineer: Kubernetes, GPUs & Pipelines

Bee Talent Solutions; Los Angeles (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

Job summary

Bee Talent Solutions seeks a Senior Platform & Infrastructure Engineer to design, build, and operate core infra and ML platforms powering Understanding Agents. You’ll focus on compute/orchestration for large-scale distributed training, simulation environments, and policy evaluation, plus CI/CD, IaC, observability, and developer tooling for production-grade systems.

You will close platform gaps, drive automation and maturity, and influence technical direction beyond your team, operating

Qualifications

• Bachelor's degree in CS or equivalent practical experience.
• 3+ years in software engineering with infra/platform/SRE focus.
• Experience operating distributed systems in production.
• Strong Kubernetes, AWS or GCP, IaC, CI/CD, and prod tooling.
• GPU compute infra experience for long-running training workloads.
• Proficiency in Python and networking fundamentals.
• Familiar with MLOps workflows: versioning, pipelines, artifacts.

Responsibilities

• Build and operate Kubernetes clusters for distributed ML bot training.
• Design infra for large-scale game simulation environments.
• Build CI/CD, deployment automation, and IaC across clouds.
• Improve platform reliability, cost efficiency, and observability.
• Develop internal APIs, control planes, and developer tooling.
• Support MLOps workflows including training pipelines and experiments.
• Manage production incidents and mentor engineers.

Skills

Kubernetes

Distributed systems

Python

Networking basics

CI/CD

AWS/GCP

MLOps

GPU compute

Education

Bachelor's degree in Computer Science or related field

Tools

Infrastructure-as-code

Job description

Bee Talent Solutions seeks a Senior Platform & Infrastructure Engineer to design, build, and operate core infra and ML platforms powering Understanding Agents. You’ll focus on compute/orchestration for large-scale distributed training, simulation environments, and policy evaluation, plus CI/CD, IaC, observability, and developer tooling for production-grade systems.

You will close platform gaps, drive automation and maturity, and influence technical direction beyond your team, operating