Machine Learning Engineer - Post Training

About the role

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.

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Company Intel

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