Senior Scientist II leading innovative AI and machine learning projects in oncology at Tempus. Collaborating with teams to advance predictive modeling and drug R&D initiatives.
About the role
- ML infra engineer tasked with building large-scale infrastructure for generative AI at Adobe. Involves extensive experience in deep learning, PyTorch, and cloud platforms.
Responsibilities
- Build and optimize infrastructures that power large foundation model training on thousands of GPUs
- Profile GPU utilization, trace inference and training runs and help craft strategies for optimizing ML model latency.
- Architect and optimize end-to-end ML pipelines, ensuring they're scalable, efficient, and robust.
- Dive deep into data to recommend the right models, evaluation metrics, and governance approaches.
- Engage in architecture, design, deployment, and optimizations of ML models and systems throughout the product lifecycle.
Requirements
- Graduate, PhD, or postgraduate degree in Computer Science, Computer Engineering, or a related field—or equivalent experience.
- 5+ years ML Engineering experience, specializing in generative AI like LLMs.
- Strong Python and deep learning engineering skills, paired with experience in training and inferencing with PyTorch or TensorFlow.
- Familiarity with distillation, transformers, and diffusion models.
- Experience with generative image and video is a plus.
- Knowledge of deployment technologies such as Docker, ML Ops, and ML services is valuable.
- Experience with cloud platforms like Azure and AWS is a plus.
- Excellent problem-solving abilities and your capacity to analyze complex issues and drive solutions with a data-driven approach.
- Strong verbal and written communication skills and success in cross-functional team environments.
Benefits
- Health insurance
- 401(k) retirement plans
- Paid time off
- Professional development opportunities
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