Machine Learning Engineer — Distillation
New
J
JobgetherArtificial Intelligence
IndiaFull-Time
SalaryCompetitive compensation package with meaningful equity opportunities.
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Job Details
- Required Skills
- Machine LearningPyTorchDeep LearningLLM
Requirements
- Strong background in machine learning, deep learning, and neural network architectures.
- Hands-on experience implementing model distillation techniques for large language models or other neural networks.
- Solid understanding of training dynamics, optimization methods, loss functions, and model evaluation.
- Experience working with PyTorch, JAX, or similar modern machine learning frameworks.
- Experience running experiments in multi-GPU or distributed training environments.
- Ability to evaluate and optimize tradeoffs between model quality, performance, latency, and cost.
- Strong programming and software engineering skills with the ability to build production-ready ML systems.
- Practical mindset focused on shipping impactful solutions rather than only theoretical research.
- Experience with inference optimization techniques such as quantization, pruning, or kernel optimization is a plus.
- Familiarity with language model evaluation methodologies is preferred.
Responsibilities
- Design and implement advanced knowledge distillation pipelines, including teacher-student approaches, self-distillation, and multi-teacher architectures.
- Distill large foundation models into smaller, faster, and more efficient models optimized for production inference.
- Run large-scale machine learning experiments to evaluate model quality, latency, efficiency, and cost tradeoffs.
- Analyze experimental results and use insights to improve model performance and optimization strategies.
- Collaborate with research teams to transform emerging distillation techniques into reliable production-ready implementations.
- Optimize training and inference performance, including memory usage, throughput, latency, and computational efficiency.
- Develop and improve internal tools, evaluation frameworks, and experiment tracking systems.
- Contribute to improving machine learning workflows and engineering best practices.
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