Principal Software Engineer - Machine Learning

We are taking a data-first approach to Machine Learning. We are building predictive analytics that are extremely easy to use by our existing data customers. We are also using ML to improve Snowflake itself using rich metadata. Last, but not least, we aim to leverage Snowflake’s data marketplace to ensure ML models won't be starved for training data.

We are hiring for an engineering owner for a major machine learning product area. Ideal candidates are strong software engineers who can understand the entire machine learning process and specialize in ML systems.

Note: We are not looking for pure data scientists.

Location: San Mateo

RESPONSIBILITIES:

• This role will help define and own a major machine learning product area. Some examples for product areas include embeddings generation and searching within Snowflake, predictive modeling for classification, building systems to convert unstructured data into structured and so on.
• Collaboratively build and execute a vision for incorporating new advances in machine learning in ways that best achieve the team’s business objectives
• Own the technical architecture to enable training, evaluation, fine-tuning and launch models that identify optimal actions and predictions
• Collaborate and influence / direct technical teams and build alignment on features key scenarios to enable ML at scale at Snowflake.
• Lead a team of ML engineers, research scientists and PMs
• Propose, design and implement the hardest parts of the product
• Debug production issues across services and multiple levels of the stack
• Support team members in delivering a high level of technical quality

IDEAL REQUIREMENTS & QUALIFICATIONS:

• Have 10+ years of software engineering experience (especially in machine learning systems)
• Have experience with building machine learning models, including neural networks, decision trees, etc.
• Experience with several of the following frameworks: SKLearn, XGBoost, PyTorch, Tensorflow
• Strong software engineering and proficiency ideally in C++ and/or Java
• Have built a roadmap and vision, and led technical decision making
• Have led multiple engineers in delivering large, high impact projects
• Have had experience shipping ML models in a large scale production environment
• Thrive in ambiguity and driving 0-1 projects
• Have worked well with data scientists, business analysts and machine learning infrastructure to connect the dots between business and technology partners
• Are a self-learner and continuously push the boundaries and state of the art around machine learning

BONUS POINTS FOR EXPERIENCE WITH THE FOLLOWING:

• Building systems for end to end machine learning lifecycle
• Building ML systems integrated into a database
• Privacy-preserving ML, e.g., Federated Learning
• Building ML-based control for a complex software system