Senior ML Engineer Platform & Integrations
Location: Los Angeles, CA
Work Model: Hybrid
About the Role
- Senior ML Engineer Platform & Integrations to join the MLBots team and help build the machine learning systems behind Client Understanding Agents.
- In this role, you will own the full lifecycle of ML systems in production from training and evaluation to deployment, serving, monitoring, and developer tooling. You will work across distributed training, GPU infrastructure, game simulation, ML evaluation, inference serving, and production systems.
- You will operate as a generalist ML Engineer, moving between ML training code, evaluation infrastructure, and production systems based on the team's priorities. This is a hands-on role with opportunities to influence technical direction and build scalable ML platforms from the ground up.
Key Responsibilities
- Build distributed training systems for Game Understanding Agents across multi-node GPU clusters.
- Integrate RL/IL frameworks and optimize training throughput, resource utilization, and convergence.
- Design and operate scalable game simulation environments for parallel rollouts, experience collection, and policy evaluation.
- Build automated and reproducible ML pipelines for data/model versioning, quality validation, experiment tracking, and lineage.
- Develop ML inference and serving systems, including model version routing, fallback mechanisms, and latency/cost/accuracy optimization.
- Build developer-facing tools, SDKs, and templates that simplify the ML agent development lifecycle.
- Establish health indicators, drift detection, training diagnostics, monitoring, and alerting aligned with SLOs.
- Troubleshoot and resolve production issues such as training instability, reward degradation, and policy regression.
- Implement governance, security, compliance, and audit controls across the ML lifecycle.
- Create clear technical documentation and contribute to engineering standards.
- Mentor junior and mid-level ML engineers.
- Participate in recruiting and technical interview processes.
Required Qualifications
- Bachelor's degree in Computer Science, related field, or equivalent practical experience.
- 3+ years of software engineering experience, with substantial experience in ML engineering, platforms, or systems.
- Proven experience operating distributed systems in production under real workloads.
- Experience with distributed training of ML agents using RL, IL, or similar agent-training paradigms.
- Strong Python skills and working knowledge of C++.
- Hands-on experience with ML frameworks such as PyTorch.
- Familiarity with distributed RL/IL frameworks such as Ray/RLlib.
- Experience with GPU-accelerated workloads, multi-node orchestration, and resource optimization.
- Ability to work across ML training, evaluation, and production infrastructure.
- Strong written communication and documentation skills.
Preferred Qualifications
- Experience with game simulation, game AI, or real-time interactive environments.
- Experience with Unreal Engine, Blueprints, or Lua.
- Background in inference serving or model evaluation frameworks.
- Experience with ML governance in production environments.
- Experience building greenfield ML platforms or self-service ML capabilities.
- Passion for games, player experience, or creative technology.
Additional Information:
AgreeYa is a global systems integrator delivering competitive advantage for its customers through software, solutions, and services. Established in 1999, AgreeYa is headquartered in Folsom, California, with a global footprint and a team of more than 2,200 staff across offices. AgreeYa works with 500+ organizations ranging from Fortune 100 firms to small and large businesses across industries such as Telecom, Banking, Financial Services & Insurance, Healthcare, Utility & Energy, Technology, Public sector, Pharma & Biotech, and others. Please visit us at for more information.
AgreeYa is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, gender identity, sexual orientation, national origin, disability, veteran status or other protected characteristics.
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