Staff Machine Learning Engineer
Develops and deploys state-of-the-art GenAI models and systems for Databricks products like Assistant and Genie. Requires 2-8 years ML engineering experience, proficiency in Python/PyTorch/TensorFlow, and expertise in LLMs.
About the job
Key Responsibilities
- Shape applied AI direction and intelligence features in products. Drive development and deployment of state-of-the-art AI models and systems (e.g., Databricks Assistant, AI/BI Genie).
- Develop novel data collection, fine-tuning, and LLM technologies for optimal task/domain performance.
- Design and implement ML pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and evaluation.
- Collaborate with AI researchers, ML engineers, and product teams to deliver impactful AI solutions.
- Build scalable backend systems, logging, telemetry, and evaluation harnesses for GenAI products.
What We’re Looking For
- 2-8 years of machine learning engineering experience in high-velocity companies, or equivalent ML research background.
- Strong track record with language modeling: generative/embedding techniques, modern architectures, fine-tuning/pre-training datasets, evaluation benchmarks.
- Proficiency in Python, TensorFlow/PyTorch, and scalable ML architectures.
- End-to-end model development from research/prototyping to deployment/monitoring.
- Strong analytical/problem-solving skills and passion for AI-driven user experiences.
- Strong coding/software engineering skills with testing, code reviews, deployment.
Bonus: LLM fine-tuning, prompt engineering, retrieval-augmented generation (RAG).
Skills
Python, PyTorch, TensorFlow, LLMs, Fine-Tuning, Machine Learning, Prompt Engineering, RAG, Ml Pipelines, Generative AI
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