Senior Machine Learning Engineer, Collaboration

Reposted 20 Days Ago
Be an Early Applicant
Menlo Park, CA
In-Office
7-9
Senior level
Artificial Intelligence • Big Data • Cloud • Machine Learning • Software • Database • Analytics
Let's build a world where data and AI turn possibilities into reality.
The Role
Design and develop core AI systems for intelligent data matching and recommendation engines. Work with advanced AI and cloud technologies to enable data-driven insights.
Summary Generated by Built In

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’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 thriving collaborative ecosystem on Snowflake that is scalable and self-reinforcing to maximize data collaboration potential.

The Opportunity

As a Senior ML Engineer, you will be instrumental in designing, developing, and deploying applications leveraging ML to power generation of data products. You will work with cutting-edge ML 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.

This is a unique opportunity to bridge ML research and production engineering, shaping 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.

  • Collaborate with cross-functional teams 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
  • 7+ 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.).

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

  • Fluency in Java or Python and SQL

  • 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

Top Skills

Cloud Platforms
Graph Databases
Java
Llms
SQL
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The Company
HQ: Bozeman, MT
8,769 Employees
Year Founded: 2012

What We Do

Snowflake powers the end-to-end data lifecycle – from ingesting and processing data to analyzing and modeling it, to building and sharing data and AI applications – helping engineers, analysts, and leaders innovate faster and achieve more with their data.

We're on a mission to empower every enterprise to achieve its full potential through data and AI.

Why Work With Us

Snowflake is where data does more, and so do you. More innovating, more growing, and more collaborating. Here, you’ll find the sweet spot between building big and moving fast, in technology and your career.

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