Senior Machine Learning Engineer - Platform and Integrations

WorkGenius Group; Santa Monica (CA); On-site; USD 124,000 - 207,000; Full time

Job summary

WorkGenius Group in Santa Monica, CA seeks a Senior Machine Learning Engineer to build and scale distributed ML training systems across multi-node GPU clusters and to integrate platform components for games.

You will develop automated pipelines, inference serving optimized for latency and cost, and create tools to accelerate the ML lifecycle, while collaborating with game teams and mentoring engineers.

Qualifications

• Bachelor’s degree in Computer Science or related field or equivalent experience with 3+ years in ML/platform/systems engineering.
• Experience operating distributed systems and production GPU workloads including distributed ML or agent training with RL/IL.

Responsibilities

• Build and operate distributed ML training systems across multi-node GPU clusters.
• Develop automated ML pipelines with data/model versioning, validation, and experiment tracking.
• Build and optimize inference-serving systems for latency, cost, and reliability.
• Create developer tools, SDKs, and templates to streamline ML lifecycle.
• Monitor system health, troubleshoot production issues, and mentor engineers.

Skills

Distributed ML

GPU Clusters

Reinforcement Learning

Imitation Learning

PyTorch

Python

C++

Ray/RLlib

Inference Serving

ML Platform Engineering

Education

Bachelor’s degree in Computer Science or related field

Tools

PyTorch

Ray

RLlib

C++

Python

Multi-node GPU orchestration

Job description

Senior Machine Learning Engineer - Platform and Integrations

Industry: Gaming

Location: Santa Monica, CA

Duration: 12 months

Responsibilities

• Build and operate distributed ML training systems across multi-node GPU clusters and scale game simulation environments for parallel rollouts, data collection, and policy evaluation.
• Develop automated ML pipelines supporting data and model versioning, validation, experiment tracking, and governance.
• Build and optimize inference-serving systems for latency, cost, accuracy, and reliability.
• Create developer tools, SDKs, and templates that streamline the ML development lifecycle.
• Monitor system health, troubleshoot production issues, improve performance, implement security controls, and mentor engineers.

Requirements

• Bachelor’s degree in Computer Science or a related field, or equivalent experience, with 3+ years of software engineering experience in ML, platform, or systems engineering.
• Experience operating distributed systems and production GPU workloads, including distributed machine learning or agent training using reinforcement learning or imitation learning.
• Strong Python skills, working knowledge of C++, and experience with PyTorch, Ray or RLlib, and multi-node GPU orchestration.
• Ability to work across ML training, evaluation, inference, and infrastructure, with experience in resource optimization, model evaluation, or ML governance.
• Strong technical communication and documentation skills; experience with game AI, game simulation, Unreal Engine, real-time interactive environments, or self-service ML platforms is desirable.

Skills

• Distributed ML
• GPU Clusters
• Reinforcement Learning
• Imitation Learning
• PyTorch
• Python
• C++
• Ray/RLlib
• Inference Serving
• ML Platform Engineering

Hourly rate is commensurate with experience and is an estimated range provided by WorkGenius.