Senior Staff Machine Learning Engineer
FlexSalary not specified
- Full Time
- Senior (5 to 8 years)
$173,000 – $264,500Compensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Cloud Computing, Data Platform, Artificial IntelligenceIndustries
Requirements
Candidates should possess a Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field, and have at least 5 years of experience in machine learning engineering. Strong experience with Python and relevant ML libraries such as TensorFlow, PyTorch, or scikit-learn is required, along with a solid understanding of statistical modeling and machine learning algorithms. Experience with cloud computing platforms, particularly Snowflake, is preferred.
Responsibilities
The Senior Machine Learning Engineer will design, build, and optimize scalable systems that power AI & ML driven solutions across Snowflake’s business data, participating in all stages of development from ideation to production. They will lead development for ML systems, operationalize ML models, architect end-to-end ML infrastructure, and develop hands-on by analyzing data, managing data quality, and designing complex ML models. Furthermore, they will collaborate across teams, champion MLOps best practices, and enable reproducibility and scale in ML development.
Skills
Machine Learning
ML Systems
Data Pipelines
Model Deployment
MLOps
Performance Optimization
Scalability
Data Engineering
Model Monitoring
CI/CD
Feature Engineering
Data Quality Management
Snowflake
Data management and analytics platform
About Snowflake
Snowflake provides a platform called the AI Data Cloud that helps organizations manage and analyze their data. This platform allows users to store and process large amounts of data efficiently, offering services like data warehousing, data lakes, data engineering, data science, and data sharing. Snowflake's system works by uniting data from different sources, enabling secure sharing and performing various types of analytics. What sets Snowflake apart from its competitors is its ability to operate seamlessly across multiple public clouds, allowing users to access their data from anywhere. The company's goal is to help businesses leverage their data for better decision-making by providing a flexible subscription-based service that scales according to their needs.
Bellevue, WashingtonHeadquarters
2012Year Founded
$1,341.3MTotal Funding
IPOCompany Stage
Data & Analytics, Enterprise Software, AI & Machine LearningIndustries
5,001-10,000Employees