Staff Applied Machine Learning Engineer

Summary

As a Staff Applied ML Engineer on the Data Team, you’ll work on the team that created Dolly LLM to build intelligent systems to democratize AI across a wide range of industries. Our teams work on some of the hardest, most interesting problems facing the business, ranging from designing large-scale distributed AI/ML systems, to optimizing distributed GPU model serving to developing novel modeling methodologies that scale to production use cases.

The Data team also functions as an in-house, production "customer" that dog foods Databricks, drives and influences the future direction of the products.

The impact you will have:

• Shape the direction of our applied ML areas and intelligence features in our products.
• Drive the development and deployment of state-of-the-art AI models and systems that directly impact the capabilities and performance of Databricks' products and services.
• Architect and implement robust, scalable ML infrastructure, including data storage, processing, and model serving components, to support seamless integration of AI/ML models into production environments.
• Develop novel data collection, fine-tuning, and pre-training strategies that achieve optimal performance on specific tasks and domains.
• Design and implement automated ML pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation, enabling rapid experimentation and iteration.
• Implement advanced model compression and optimization techniques to reduce the resource footprint of language models while preserving their performance.
• Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps.
• Contribute to the broader AI community by publishing research, presenting at conferences, and actively participating in open-source projects, enhancing Databricks' reputation as an industry leader.
• Mentor and guide junior ML engineers on the team by helping with project planning, technical decisions, and code and document review.

What we look for:

• 7+ years of machine learning engineering experience in high velocity, high-growth companies
• Experience developing AI/ML systems at scale in production or in high-impact research environments.
• Strong track record of working with language modeling technologies. This could include the following: Developing generative and embedding techniques, modern model architectures, fine tuning / pre-training datasets, and evaluation benchmarks.
• Strong coding and software engineering skills, and familiarity with software engineering principles around testing, code reviews and deployment.
• Experience deploying and scaling language models in production; deep understanding of the unique infrastructure challenges posed by training and serving LLMs.
• Strong understanding of computer science fundamentals.
• Contributions to well-used open-source projects.

Benefits

• Comprehensive health coverage including medical, dental, and vision
• 401(k) Plan
• Equity awards
• Flexible time off
• Paid parental leave
• Family Planning
• Gym reimbursement
• Annual personal development fund
• Employee Assistance Program (EAP)

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks utilizes the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Local Pay Range

$192,000—$260,000 USD