Where Data Does More. Join the Snowflake team.

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

The following represents the expected range of compensation for this role:

The estimated base salary range for this role is $157,000 - $230,000.
Additionally, this role is eligible to participate in Snowflake’s bonus and equity plan.

The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. This role is also eligible for a competitive benefits package that includes: medical, dental, vision, life, and disability insurance; 401(k) retirement plan; flexible spending & health savings account; at least 12 paid holidays; paid time off; parental leave; employee assistance program; and other company benefits.

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
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

Benefits

The estimated base salary range for this role is $157,000 - $230,000
Additionally, this role is eligible to participate in Snowflake’s bonus and equity plan
The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location
This role is also eligible for a competitive benefits package that includes: medical, dental, vision, life, and disability insurance; 401(k) retirement plan; flexible spending & health savings account; at least 12 paid holidays; paid time off; parental leave; employee assistance program; and other company benefits

Responsibilities

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
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

Software Engineer, Machine Learning – Engineering Systems and AI Research

Job Type