ML Engineer - Pre Training - Remote

Overview

The ML Engineer - Pre Training will design and optimize large-scale pre-training systems that power Mindbeam’s generative AI models.

In Short

• Build scalable pre-training pipelines for foundation models.
• Implement distributed training strategies across GPUs/TPUs.
• Collaborate with researchers for production-ready workflows.
• Develop monitoring and fault-tolerance systems.
• Benchmark and tune performance across hardware and software stacks.
• Requires a Bachelor’s, Master’s, or PhD in Computer Science or related field.
• 2+ years of experience with large-scale model training.
• Strong coding skills in Python and familiarity with ML frameworks.
• Experience with GPU scheduling and memory optimization.
• Comfort with containerized environments like Docker/Kubernetes.

Requirements

• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or related field.
• 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.

Benefits

• Opportunity to work on cutting-edge AI technologies.
• Collaborative and innovative work environment.
• Flexible working hours.
• Access to state-of-the-art resources and tools.
• Professional growth and development opportunities.