We are seeking experienced Machine Learning Engineers to support an AI training project involving model development, training and inference systems, numerical computing, and performance optimization.
This is a coding-intensive role focused on building, debugging, reviewing, and validating challenging machine learning engineering tasks using Python and coding agents.
Key Responsibilities
• Develop and validate machine learning models, training pipelines, and inference systems.
• Implement model components, data pipelines, evaluation frameworks, and numerical methods.
• Build reproducible workflows using Python and command-line tools.
• Optimize model performance, memory usage, and processing throughput.
• Debug numerical, software, and system-level failures.
• Verify implementations against objective correctness and performance requirements.
Required Qualifications
• A Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a related quantitative field.
• Strong professional or research experience in machine learning.
• Practical proficiency in Python and coding agents.
• Experience developing, testing, and debugging machine learning systems.
Relevant tools include:
• PyTorch and JAX
• NumPy and SciPy
• SGLang, vLLM, and llama.cpp
• Hugging Face Transformers and Tokenizers
Preferred Qualifications
• Experience at a recognized technology company, AI laboratory, research organization, or engineering environment.
• Strong academic or open-source contributions in machine learning.
• Experience with model training, inference optimization, numerical computing, and reproducible engineering workflows.
Compensation
• $80-$150/hour, with output-based payment for tasks that meet project specifications.
• Approximately 15 hours per week.
• Minimum submission requirements apply.
• Approximately 100 openings available.
Candidates should be available to start immediately, as positions are typically filled within 48 hours.