Senior Data Scientist, Machine Learning

Company: Serve Operating Co
Location: Redwood City, CA
Position Type: Full Time
Experience: 5 years
Education: Bachelor's
Prototype and train learning-based models using a data-centric approach, applying techniques such as automated feature engineering, active learning, and fine-tuning on curated datasets; Design, develop, and maintain efficient data and feature extraction pipelines to support ML engineers in accessing high-quality data for model training; Design auto labeling system using ensemble of models that can reason from multimodal data for different use-cases, including image semantic labeling using vision grounded models, intent and path prediction ground truth; Perform complex data extraction, transformation, and loading (ETL) processes, ensuring data is clean, accessible, and well-documented; Write and optimize high quality SQL queries for data analysis and ingestion from various sources; Partner with data infrastructure and ML engineers to ensure seamless integration of data and machine learning workflows; and Produce high-quality, maintainable code and participate in peer code reviews to share knowledge and uphold team standards. Position allows 100% telecommuting from anywhere in the U.S. Salary: $194,834 - $218,284 per year. MINIMUM REQUIREMENTS: Bachelor’s Degree or U.S. equivalent in Computer Science, Data Science, or a related field, plus 5 years of professional experience as a Data Scientist, Machine Learning Engineer, Data Engineer, or any occupation, job title, or position performing software engineering and machine learning. Must also have the following special skills: 5 years of professional experience utilizing SQL to write and optimize complex queries for extraction, analysis, and ingestion of structured, semi-structured, and unstructured data; 5 years of professional experience utilizing machine-learning frameworks (including TensorFlow and PyTorch); 5 years of professional experience designing and developing data and feature extraction pipelines, including pipelines for multi-modal data (including images, point clouds, or time-series); 5 years of professional experience training and prototyping machine-learning models using data-centric techniques including automated feature engineering, active learning, and fine-tuning; 5 years of professional experience utilizing cloud platforms including AWS, GCP, or Azure; 5 years of professional experience utilizing containerization and workflow tools including Docker, Kubernetes, or Airflow; 5 years of professional experience collaborating with cross-functional engineering teams to integrate data pipelines and ML workflows; 3 years of professional experience programming in Python, building scalable data pipelines, or implementing ETL workflows; and 1 year of professional experience working with relational databases and SQL (including Postgres, Redshift, or SQL Server). CONTACT: Please send resume to hr@ serverobotics.com Must specify Ad Code SDSB in the subject line.