Senior Data Scientist, Machine Learning in United States at Jobgether
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Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist, Machine Learning based in the United States.
In this role, you will contribute to the development of advanced machine learning systems that power next-generation robotic delivery solutions in complex urban environments. You will work at the intersection of robotics, computer vision, and data science to build models that enable autonomous navigation, intelligent decision-making, and multimodal perception. This is a highly hands-on position where you will design data-centric ML workflows, build scalable feature extraction pipelines, and prototype models using large, diverse datasets. You will collaborate closely with ML engineers, data infrastructure teams, and robotics specialists to ensure seamless integration between data systems and production models. Your work will directly impact real-world deployments across multiple major U.S. cities, helping transform how goods are delivered in dense urban settings. The environment is fast-paced, highly collaborative, and deeply engineering-driven, with a strong emphasis on experimentation and real-world performance.
- Design, prototype, and train machine learning models using data-centric approaches such as automated feature engineering, active learning, and model fine-tuning on curated datasets.
- Develop and maintain scalable data pipelines and feature extraction systems supporting high-quality datasets for model training and inference.
- Build and optimize ETL workflows to ensure structured, semi-structured, and unstructured data is clean, accessible, and production-ready.
- Design and implement auto-labeling systems leveraging ensemble and vision-based models for multimodal datasets including images, spatial, and time-series data.
- Write and optimize advanced SQL queries for data extraction, transformation, and analysis across multiple data sources.
- Partner with ML engineers and data infrastructure teams to integrate machine learning workflows into scalable production systems.
- Collaborate across engineering teams to ensure high-quality, maintainable code and participate in peer code reviews.
- Bachelor’s degree in Computer Science, Data Science, or a related field (or U.S. equivalent).
- 5+ years of professional experience as a Data Scientist, Machine Learning Engineer, Data Engineer, or similar role involving ML and software engineering.
- Strong expertise in SQL with experience writing and optimizing complex queries across structured and unstructured datasets.
- Hands-on experience with machine learning frameworks such as TensorFlow and PyTorch.
- Proven experience designing data and feature extraction pipelines, including multimodal datasets such as images, point clouds, or time-series data.
- Strong background in training and prototyping ML models using techniques such as active learning, automated feature engineering, and fine-tuning.
- Experience working with cloud platforms such as AWS, GCP, or Azure.
- Strong proficiency in Python and experience building scalable data pipelines and ETL workflows.
- Experience with containerization and orchestration tools such as Docker, Kubernetes, or Airflow.
- Proven ability to collaborate in cross-functional engineering environments to deliver integrated ML systems.
- Experience working with relational databases such as Postgres, Redshift, or SQL Server.
- Competitive salary ranging from $194,834 to $218,284 annually.
- 100% remote work flexibility across the United States.
- Opportunity to work on real-world robotics and autonomous delivery systems deployed in major U.S. cities.
- Exposure to cutting-edge machine learning, computer vision, and multimodal AI applications.
- Collaborative, engineering-driven environment with strong emphasis on innovation and experimentation.
- Opportunity to contribute to large-scale ML systems with direct real-world impact.
- Inclusive, cross-disciplinary team culture focused on solving complex urban mobility challenges.