- Explore and analyze performance bottlenecks in ML training and inference
- Design, implement and benchmark libraries and methods to overcome aforementioned bottlenecks
- Build tools for performance profiling, analysis, and estimation for ML training and inference
- Balance the tradeoff between performance and usability for our customers
- Facilitate our community through documentation, talks, tutorials, and collaborations
- Collaborate with external researchers and leading AI companies on various efficiency methods
- Hands on experience the internals of deep learning frameworks (e.g. PyTorch, TensorFlow) and deep learning models
- Experience with high-performance linear algebra libraries such as cuDNN, CUTLASS, Eigen, MKL, etc.
- General experience with the training and deployment of ML models
- Experience with compiler technologies relevant to machine learning
- Experience with distributed systems development or distributed ML workloads
- Hands on experience with writing CUDA code and knowledge of GPU internals (Preferred)
- Publications in top tier ML or System Conferences such as MLSys, ICML, ICLR, KDD, NeurIPS (Preferred)
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GenAI Staff Machine Learning Engineer, Performance Optimization - San Francisco, United States - Databricks
Description
P-984
Founded in late 2020 by a small group of machine learning researchers, Mosaic AI enables companies to create state-of-the-art AI models from scratch on their own data. From a business perspective, Mosaic AI is committed to the belief that a company's AI models are just as valuable as any other core IP, and that high-quality AI models should be available to all. From a scientific perspective, Mosaic AI is committed to reducing the cost of training state-of-the-art models - and sharing our knowledge about how to do so with the world - to allow everyone to innovate and create models of their own.
Now part of Databricks since July 2023 as the GenAI Team, we are passionate about enabling our customers to solve the world's toughest problems by building and running the world's best data and AI platform. We leap at every opportunity to solve technical challenges, striving to empower our customers with the best data and AI capabilities.
You will:
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
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide - including Comcast, Cond Nast, Grammarly, and over 50% of the Fortune 500 - rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache SparkTM, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
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