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Snowflake

Software Engineer, Machine Learning – Engineering Systems and AI Research

Reposted 13 Days Ago
In-Office
2 Locations
160K-230K Annually
Mid level
In-Office
2 Locations
160K-230K Annually
Mid level
Join the Snowflake team to design, implement, and optimize machine learning systems that impact developer productivity and platform efficiency. Collaborate with diverse teams on ML tools and infrastructure while enhancing software engineering practices.
The summary above was generated by AI

Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level.

We are seeking a Software Engineer to join a joint R&D initiative between the Engineering Systems Team and Snowflake AI Research team. This team drives innovation at the intersection of machine learning and developer productivity, with flagship projects such as ML-powered test systems and LLM-powered code review and automation tools. The team supports both product-facing ML initiatives and internal systems optimization, accelerating Snowflake’s thought leadership and operational excellence in enterprise AI.

This role is ideal for candidates who can span the functions of data scientist and research scientist, while maintaining robust software engineering practices and collaborating with diverse stakeholders—using internal research to power real-world, production-ready ML solutions.

Key Responsibilities
  • Partner across research and engineering to design, implement, and maintain machine learning systems that directly impact developer workflows and core platform efficiency.

  • Develop, evaluate, and deploy ML models for automation in CI/CD pipelines, using real-world code and data from large, complex codebases.

  • Build and optimize LLM-based tools for code review, quality automation, and developer assistance, from research prototype to robust production deployment.

  • Contribute to the improvement of internal ML and data tooling, pipelines, and collaboration between AI Research and Engineering Systems.

  • Collaborate on open-source releases, research publications, and developer community engagement efforts.

  • Operate across the software lifecycle: requirements, design, implementation, delivery, testing, iteration, and support.

  • Contribute to a culture of innovation, excellence, and inclusion in a collaborative and fast-paced environment.

Minimum Qualifications
  • PhD or Master’s degree in Computer Science, Engineering, Statistics, or a related technical field, with research or industry experience in real-world machine learning applications.

  • Proficiency in Python and core ML/data science frameworks including Pandas, NumPy, Scikit-Learn, XGBoost, PyTorch, and related ecosystem tools.

  • Demonstrated hands-on experience solving applied ML problems end-to-end: data ingestion/preprocessing, feature and model selection, training, evaluation (with best practices on versioning, bias, and validation), deployment, and monitoring.

  • Strong software engineering fundamentals: code quality, reproducibility, CI/CD best practices, debugging, testing, and documentation.

  • Familiarity with ML operations (MLOps), data/feature versioning, and collaborative software development (Git, containers, etc.).

  • Strong communication and teamwork skills; able to describe technical tradeoffs and engage both research scientists and software engineers.

Bonus Qualifications
  • Experience with large-scale language models (LLMs), agentic/autoML systems, or ML for developer productivity (e.g., code intelligence, automated testing, static analysis).

  • 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.

Why Join Us

This is a rare opportunity to collaborate across Snowflake’s leading AI research and engineering system organizations, shaping the next generation of intelligent developer tools and ML-powered infrastructure. You’ll work with world-class researchers and engineers, operate at scale, and have impact across both the open-source community and internal Snowflake engineering.

The role offers career development opportunities in ML engineering, research, and advanced software systems, in a values-driven, inclusive environment that values curiosity, impact, and technical excellence.

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

Top Skills

Git
Mlops
Numpy
Pandas
Python
PyTorch
Scikit-Learn
Xgboost

Snowflake Dublin, California, USA Office

4140 Dublin Blvd., Dublin, CA, United States, 94568

Snowflake Menlo Park, California, USA Office

135 Constitution Dr, Menlo Park, CA, United States, 94025

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