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Principal Software Engineer - Machine Learning
$243,000 - 379,500
Snowflake
Garland Drive 125, Menlo Park
$243,000 - 379,500
Requirements
Must:
- Over 10 years of experience in developing large-scale AI/ML systems, with a proven track record as a Principal Engineer focused on ML developer tools and platforms.
- A strong passion for AI/ML infrastructure and the applications of large language models (LLMs).
- In-depth understanding of building end-to-end customer-facing products, with experience collaborating with cross-functional teams, research teams, and product managers.
- Robust computer science fundamentals, including expertise in data structures, algorithms, and distributed systems (proficiency in Python or Java is preferred).
- Familiarity with machine learning and deep learning frameworks such as PyTorch, XGBoost, etc. (expertise is preferred).
- A bachelor's, master's, or PhD in Computer Science or related fields.
Responsibilities
- Develop AI-based services and platforms for machine learning that are customer-focused.
- Design and implement highly scalable distributed platforms within the global Snowflake framework.
- Engage in decision-making processes regarding both technical and business matters.
- Collaborate with engineers across various teams to drive cross-functional initiatives to completion.
- Ensure the operational readiness of services, meeting reliability, availability, and performance commitments to our customers.
Description
At Snowflake, we are on a mission to shape the future of machine learning and AI by crafting state-of-the-art infrastructure and AI-powered agents. Our goal is to enable users to easily build and deploy powerful models directly on their data while tackling real-world ML challenges at scale. We are striving to create highly integrated products that are user-friendly, secure, and scalable, facilitating seamless end-to-end ML workflows. We are expanding rapidly and seeking individuals who align with our values, question conventional thinking, and drive the pace of innovation as we build a future for both themselves and Snowflake. For positions based in the United States, please refer to the Snowflake Careers Site for detailed salary and benefits information. The expected salary range for this role is between $243,000 and $379,500, and it is eligible for participation in Snowflake’s bonus and equity plans. The starting salary will be determined based on relevant, non-discriminatory factors such as skills, experience, and location. This position also comes with a competitive benefits package that includes medical, dental, and vision insurance, a 401(k) plan, flexible spending and health savings accounts, a minimum of 12 paid holidays, paid time off, parental leave, and other company perks. We look forward to how you will make your impact!
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You can find Machine Learning Engineer salaries in the United States here.
How many Machine Learning Engineer jobs are in the United States?
Currently, there are 985 ML, AI openings. Check also: TensorFlow jobs, Python jobs, Computer-Vision jobs - all with salary brackets.
Is the US a good place for Machine Learning Engineers?
The US is one of the best countries to work as a Machine Learning Engineer. It has a vibrant startup community, growing tech hubs and, most important: lots of interesting jobs for people who work in tech.
Which companies are hiring for Machine Learning Engineer jobs in the United States?
LGS, une Société IBM / an IBM Company, Technology Service Professionals, Inc, Capgemini, Johnson Health Tech North America Inc, Navy Federal Credit Union, Wayne-Sanderson Farms, Idaho Central Credit Union among others, are currently hiring for ML, AI roles in the United States.
The company with most openings is Leidos as they are hiring for 117 different Machine Learning Engineer jobs in the United States. They are probably quite committed to find good Machine Learning Engineers.
The company with most openings is Leidos as they are hiring for 117 different Machine Learning Engineer jobs in the United States. They are probably quite committed to find good Machine Learning Engineers.