ML Training Optimization Engineer — Scale Large Models (Equity)

Featherless AI; Poland; Remote; PLN 180,000 - 260,000; Full time

Benefits offered by this job

Competitive compensation

Meaningful equity

Job summary

A technology start-up in Poland is seeking an experienced ML Engineer focused on training optimization to enhance large-scale model training. In this high-impact role, you will optimize training pipelines for speed and cost while closely collaborating with researchers. The ideal candidate has strong experience in training large neural networks and is proficient in PyTorch. The role offers competitive compensation and equity in a fast-paced startup environment.

Qualifications

• Strong experience training large neural networks (LLMs or similarly large models).
• Hands-on experience with training optimization (not just model usage).
• Solid understanding of backpropagation, optimization algorithms, and training dynamics.

Responsibilities

• Optimize large-scale model training pipelines.
• Improve distributed training strategies.
• Tune optimizers, schedulers, and precision.
• Reduce training time and compute cost.
• Collaborate with researchers on architecture-aware training strategies.

Skills

Training optimization

Backpropagation

Optimization algorithms

Distributed systems for ML training

PyTorch

Job description

A technology start-up in Poland is seeking an experienced ML Engineer focused on training optimization to enhance large-scale model training. In this high-impact role, you will optimize training pipelines for speed and cost while closely collaborating with researchers. The ideal candidate has strong experience in training large neural networks and is proficient in PyTorch. The role offers competitive compensation and equity in a fast-paced startup environment.