See how your profile stacks up against this role.
We compared the job requirements to your profile to show where you're strong and where you fall short.
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.
After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.
Marcus Rivera
Chief Revenue Officer
B&D Industries, Inc.
Blue River Tech Partners
Blue River Technology
Clera Inc.
Clera
Mindbeam AI
Mindbeam AI
Mindbeam AI
