Principal Software Engineer - Machine Learning
Build the future of data. Join the Snowflake team.
Snowflake is still not ready to stop innovating. Next, 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 ML frameworks, tools, algorithms, and selected applications. Ideal candidates are strong software engineers who can leverage machine learning modeling, including data analysis, statistical modeling and also build ML systems and production quality software. Location: San Mateo
- This role will help define and own the roadmap, working collaboratively and proactively with senior architects, PMs and team leadership. The initiatives include deep learning modeling, predictive data, automation, and/or user experience and accessibility to predictive analytics via Snowflake
- Collaboratively build and execute a vision for incorporating new advances in machine learning in ways that best achieve the team’s business objectives
- Design, train, evaluate, improve, and launch models that identify optimal actions and predictions
- Debug production issues across services and multiple levels of the stack
- Collaborate across ML Platform and other partner teams to continuously improve ML development velocity and capabilities at Snowflake
- 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 5+ years of building machine learning models, including deep learning, time series analytics, etc.
- Experience with several of the following frameworks: SKLearn, XGBoost, PyTorch, Tensorflow
- Have built a roadmap and vision around machine learning teams, and led technical decision making with help of architects and PMs and team
- Have led multiple engineers in delivering large, high impact projects
- Strong software engineering and productive developer in Python (Java/C++ is a plus)
- Have had experience shipping ML models in a large scale production environment
- 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 ML algorithms for database systems
- Privacy-preserving ML, e.g., Federated Learning
- Building ML-based control for a complex software system
- Building systems for model understanding
- ML tuning and feature selection algorithms
- PhD degree in Computer Science with specialization in Machine Learning
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