Machine Learning Engineer - Pre Training

Role Overview

Design and optimize large-scale pre-training systems that power Mindbeam’s generative AI models. Build scalable pre-training pipelines for foundation models, optimizing throughput and efficiency.

What You Will Do

Implement distributed training strategies across GPUs/TPUs and high-performance clusters. Develop monitoring and fault-tolerance systems to ensure reliable large-scale training. Continuously benchmark and tune performance across hardware and software stacks.

Why It Might Be a Fit

You thrive on scale and complexity. You enjoy solving system-level bottlenecks, pushing hardware and software to their limits, and working closely with researchers to accelerate cutting-edge AI development.

Requirements

• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or related field—or equivalent experience
• 2+ years of experience with large-scale model training and distributed systems
• Strong coding skills in Python and familiarity with ML frameworks (PyTorch, TensorFlow, JAX)
• Experience with GPU scheduling, memory optimization, and parallelism strategies
• Comfort with containerized and orchestrated environments (Docker/Kubernetes)
• Understanding of high-performance computing and networking bottlenecks