Software Engineer, Machine Learning - Engineering Systems and AI Research

About the Role

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.

Requirements

• 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.

Nice to Have

• 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.

Qualifications

• Educational background with a PhD or Master's degree in a relevant technical field.

Benefits & Perks

• Competitive salary with an estimated range of $157,000 - $230,000.
• Eligibility to participate in Snowflake's bonus and equity plan.
• Comprehensive benefits package including 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.