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Remote Senior Data Scientist, Machine Learninggrabjobs • United States
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Remote Senior Data Scientist, Machine Learning

grabjobs
  • US
    United States
  • US
    United States
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Über

At Serve Robotics, we’re reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It’s designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses. The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.
Who We Are
We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully. 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 highquality, 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,
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
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.
  • United States

Sprachkenntnisse

  • English
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