Senior Machine Learning Data Engineer - Cambridge

Motion Recruitment; Cambridge (MA); On-site; USD 130,000 - 185,000; Full time

Benefits offered by this job

Bonus or Commission Eligible

Medical Insurance

Dental Benefits

Vision Benefits

Paid Time Off

401(k) with match

Job summary

Motion Recruitment is seeking a Senior Machine Learning Data Engineer in Cambridge, MA, to build and manage data pipelines powering robotic AI systems. You will enable image, video, and sensor data workflows for model training and evaluation.

The role is hands-on, partnering with ML engineers and product teams to improve data quality, labeling, feature generation, and data versioning in a cutting-edge robotics environment.

Qualifications

• Proven experience building ML data pipelines for large workloads.
• Experience with Python and SQL for data engineering tasks.
• Experience with large-scale image/video/sensor datasets.
• Familiarity with Spark or Ray for data processing.
• Experience with AWS cloud platforms and ML data storage.
• Understanding of data modeling and storage for ML applications.
• Experience building ETL workflows and automation.
• Familiarity with ML lifecycle concepts and experimentation.
• Experience with version control and software engineering best practices.
• Strong problem-solving and analytical skills.

Responsibilities

• 100% Hands On.
• Build and maintain machine learning data pipelines supporting robotics and AI initiatives.
• Develop processes that prepare image, video, and sensor datasets for model training.
• Partner with ML teams to improve training data quality and accessibility.
• Design scalable storage and retrieval solutions for large unstructured datasets.
• Create data validation processes that improve model reliability.
• Support feature engineering, experimentation, and dataset generation workflows.
• Implement automation to reduce manual data preparation and curation.
• Monitor data pipelines and resolve issues impacting model development.
• Optimize data processing workflows for performance and scalability.
• Contribute to ML infrastructure and data best practices.

Skills

Python

SQL

Data pipelines

ML datasets

Spark

Ray

AWS

Data modeling

ETL

ML lifecycle

Version control

Education

Bachelor's degree in Computer Science, Data Engineering, Engineering, Mathematics, or related field

Tools

Spark

Ray

AWS

Job description

Job Description

A fast-growing robotics company is seeking a Senior Machine Learning Data Engineer to help develop the data foundation that powers intelligent robotic systems operating in high-throughput logistics environments. The organization builds AI-driven automation solutions that leverage computer vision, machine learning, and robotic manipulation to solve complex real-world challenges involving package handling, object identification, and operational optimization.

As a Senior Machine Learning Data Engineer, you will focus on the collection, preparation, management, and delivery of data used to train, evaluate, and improve machine learning models. Unlike traditional data engineering positions that concentrate on analytics, reporting, or platform infrastructure, this role is centered on enabling AI and computer vision teams to build more accurate and effective robotic systems.

You will work closely with machine learning engineers, roboticists, software developers, and product teams to create scalable data pipelines capable of handling large volumes of image, video, sensor, and operational data. The ideal candidate enjoys solving challenges surrounding data labeling, feature generation, model training datasets, data versioning, and machine learning infrastructure. This role offers the opportunity to directly influence how AI systems learn and improve within a cutting-edge robotics environment.

Required Skills & Experience

• Strong proficiency with Python and SQL
• Experience building data pipelines for machine learning workloads
• Experience working with large-scale image, video, or sensor datasets
• Knowledge of data processing frameworks such as Spark or Ray
• Experience with cloud platforms such as AWS
• Understanding of data modeling and storage solutions for ML applications
• Experience building ETL workflows and automation solutions
• Familiarity with machine learning lifecycle concepts
• Experience with version control and software engineering best practices
• Strong problem-solving and analytical skills

Desired Skills & Experience

• 5+ years of Data Engineering or Machine Learning Infrastructure experience
• Experience supporting computer vision or AI-focused teams
• Robotics, automation, or industrial technology experience
• Familiarity with model training workflows and feature engineering
• Experience with annotation platforms and data labeling operations
• Knowledge of MLOps tools and practices
• Experience working with unstructured datasets
• Bachelor's degree in Computer Science, Data Engineering, Engineering, Mathematics, or a related field

What You Will Be Doing

Daily Responsibilities

• 100% Hands On
• Build and maintain machine learning data pipelines supporting robotics and AI initiatives
• Develop processes that prepare image, video, and sensor datasets for model training
• Partner with machine learning teams to improve the quality and accessibility of training data
• Design scalable storage and retrieval solutions for large unstructured datasets
• Create data validation processes that improve model reliability and performance
• Support feature engineering, experimentation, and dataset generation workflows
• Implement automation that reduces manual effort in data preparation and curation
• Monitor data pipelines and resolve issues impacting model development
• Optimize data processing workflows for performance and scalability
• Contribute to the evolution of machine learning infrastructure and data best practices

The Offer

• Bonus OR Commission eligible

You will receive the following benefits

• Medical Insurance
• Dental Benefits
• Vision Benefits
• Paid Time Off (PTO)
• 401(k) (including match, if applicable)

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.

Posted By: Nick Ramler