Dice is the leading career destination for tech experts at every stage of their careers. Our client, HireTeq, is seeking the following. Apply via Dice today! Machine Learning Engineer Location: Los Altos, CA (Hybrid) Term: 3-month contract (potential to extend/go FTE) Job Content: • 4+ years of professional ML engineering experience at an AI/ML-focused organization. • Familiarity with the state-of-the-art in behavior learning, language, and/or computer vision. • Experience training large-scale foundation models (VLMs, text-to-video models, etc) utilizing distributed training and high-performance optimization techniques such as quantization, mixed precision, model parallelism, data parallelism or FSDP. • Extensive practical experience with PyTorch. • Strong proficiency in Python and software development best practices such as unit testing, documentation, code review, continuous integration, and dependency management. • Familiarity with data pipelines, model serving and optimization, cloud training, and dataset management. • An ability to move fast and switch between modes of rapid prototyping and robust implementation as required. Nice to have: • Experience deploying models on embodied systems/robots. • Experience working in mixed teams of research scientists and engineers. • Experience Amazon EC2, S3, and/or Sagemaker. • Experience with Bazel. Key Qualifications & Requirements • Automotive Domain Expertise Proven track record in AI/ML applications within the automotive sector (highest priority). • PyTorch Mastery Hands-on experience in building, training, and deploying models using PyTorch. • AI/ML Engineering Experience 4+ years in professional machine learning engineering, ideally within AI/ML-focused organizations. • Cutting-Edge Research Familiarity Knowledge of the latest advancements in behavior learning, language modeling, and/or computer vision. • Large-Scale Model Training Expertise in training foundation models (VLMs, text-to-video, etc.) with distributed training and high-performance optimization techniques (quantization, mixed precision, model/data parallelism, FSDP). • Software Engineering Excellence Strong proficiency in Python with best practices including unit testing, documentation, code review, CI/CD, and dependency management. • End-to-End AI Workflow Knowledge Experience in data pipelines, model serving & optimization, cloud-based training, and dataset management. • Agility & Adaptability Ability to rapidly prototype and transition to production-grade implementations as project needs evolve.