ML Engineer, Collaboration
SnowflakeWhere Data Does More. Join the Snowflake team.
We’re at the forefront of the data revolution, committed to building the world’s greatest data and applications platform. Snowflake started with a clear vision: develop a cloud data platform that is effective, affordable, and accessible to all data users. Data Cloud allows sharing live data in governed and secure ways so our customers can solve their business problems. We’re building a collaboration forum for data consumers and providers to exchange and collaborate on data within an organization.
The Opportunity
As ML Engineer, you will be instrumental in designing, developing, and deploying applications leveraging AI to build data products. You will work with cutting-edge LLMs and advanced data processing techniques to transform complex metadata into actionable insights, enabling our users to discover and leverage data like never before. This is a unique chance to shape a product that fundamentally changes how organizations collaborate on data.
Key Responsibilities
Design, build, and maintain end-to-end ML pipelines, including data preprocessing, feature engineering, prompt engineering, evaluation, and deployment.
Apply domain knowledge where applicable to identify opportunities for applying ML to real-world problems.
Monitor, evaluate and improve agent performance
Stay up to date with research, frameworks, and techniques in ML/AI to apply where relevant
Minimum Qualifications
3+ years of industry experience designing, building, and supporting backend large-scale data processing systems in production
Strong software engineering fundamentals: code quality, reproducibility, CI/CD best practices, debugging, testing, and documentation.
Proficiency in Python and core ML/data science frameworks such as Pandas, NumPy, Scikit-Learn, XGBoost, PyTorch, and related ecosystem tools.
Understanding of modern ML applications, including deploying Gen-AI/LLM-based solutions with techniques like RAG, prompt chaining, or agentic workflows
Demonstrated hands-on experience solving applied ML problems end-to-end: data ingestion/preprocessing, feature and model selection, training, evaluation , deployment, and monitoring.
Familiarity with ML operations (MLOps), data/feature versioning, and collaborative software development (Git, containers, etc.).
Fluency in Java or Python and SQL
Strong communication and teamwork skills; able to describe technical tradeoffs and engage both research scientists and software engineers.
BS/MS/PHD in Computer Science or related majors, or equivalent experience
Bonus Qualifications
Familiarity with different types of machine learning approaches (supervised, reinforcement learning, contrastive learning) and their practical constraints in large-scale, dynamic code environments
Contributions to open source ML/AI projects or scientific publications; Participations in AI/ML competitions (e.g., Kaggle)
Experience working in or with developer-facing infrastructure, build/test automation, or productionizing research prototypes
Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.
Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
Compensation Range: $157K - $230K