Machine Learning Engineer - Post Training

About Mindbeam

We are building the next-generation AI infrastructure for both open-source and enterprise applications. Our work is deeply research-oriented and passionate about developing ground-breaking innovations to take state-of-the-art AI applications to the next level.

Mission

Advance AI performance and efficiency by engineering systems for fine-tuning, evaluation, and deployment at scale.

Role Expectations

• Develop pipelines for post-training tasks such as fine-tuning, evaluation, and model compression.

• Implement scalable systems for model deployment, monitoring, and optimization.

• Collaborate with researchers to validate experimental results in production contexts.

• Build tools to automate benchmarking and regression testing.

• Identify opportunities to improve efficiency in resource utilization and inference speed.

Background

• Bachelor’s, Master’s, or PhD in Computer Science, ML/AI, or related field—or equivalent practical experience.

• 2+ years of experience in model training, evaluation, or deployment.

• Strong skills in Python, ML frameworks (PyTorch/TensorFlow), and data pipeline tools.

• Familiarity with optimization techniques (quantization, pruning, distillation).

• Hands-on experience deploying models on cloud and/or GPU infrastructure.

• Knowledge of monitoring and observability tools.

About You

You combine deep technical expertise with a pragmatic mindset. You thrive on bridging research and production, and you’re motivated by the challenge of making cutting-edge models usable and efficient at scale.