Senior ML Systems Engineer

About A5 Labs

A5 Labs is a US-based, fully remote AI and gaming technology company.

We build large-scale systems behind competitive online games, focusing on AI-driven gameplay, simulation, analytics, and security (anti-cheat).

Our work sits at the intersection of C++ systems, machine learning infrastructure, and large-scale data pipelines, enabling researchers and engineers to iterate quickly and deploy models reliably in production.

Role Summary

We are looking for a senior ML systems engineer to design, build, and optimize the end-to-end infrastructure that connects:

• C++ game environments and inference serving
• Python-based training, evaluation, and analytics pipelines

This role is systems- and performance-oriented, not an algorithm research position.

Your impact will be enabling fast iteration, scalable training, and reliable deployment across the entire ML/RL stack.

What You’ll Do

• Design and maintain end-to-end ML/RL systems spanning:
• C++ game environments and real-time inference serving
• Python-based training, evaluation, and data pipelines
• Build and optimize high-throughput data pipelines that serve:
• RL training
• evaluation and visualization
• gameplay analytics
• anti-cheat models and research workflows
• Profile and optimize system performance (latency, throughput, memory, GPU utilization) across C++ and Python components.
• Design infrastructure that enables fast iteration from small-scale experiments to large-scale training and production.
• Improve observability by building tools for:
• logging and metrics
• replaying problem cases
• debugging model and system behavior
• Establish engineering standards for ML systems:
• testing
• CI/CD
• coding and operational guidelines

Ideal Experience

• Strong experience with C++ systems, including implementation, profiling, and optimization.
• Experience building ML training and evaluation pipelines in Python.
• Experience designing systems that bridge data generation (env / serving) and model training.
• Solid understanding of ML/RL workflows (training, evaluation, inference); algorithm research is not the focus.
• Experience with production ML systems, CI/CD, and test automation.
• Bonus:
• experience with simulation, game engines, or real-time inference systems
• experience supporting researchers with scalable infrastructure

Typical Problems You’ll Work On

• How do we design a system where a C++ game environment efficiently feeds data to training, evaluation, analytics, and anti-cheat pipelines?
• How do we profile and optimize the end-to-end loop from environment → data → training → inference?
• How do we enable researchers to explore new ideas without heavy infrastructure overhead?
• How do we build observability tools that expose both model behavior and system bottlenecks?
• How do we ensure fast, reliable, and scalable C++ inference serving in production?

Tech Stack

• C++ (game environments, inference serving)
• Python (training, evaluation, data pipelines)
• TypeScript / React (internal tools and visualization)

Location & Compensation

• Fully remote
• Competitive salary + performance-based bonuses