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Machine Learning Data Engineer Jobs (NOW HIRING)

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Machine Learning Data Engineer

Seattle, WA · Remote

$130K - $160K/yr

Qualifications: * 3+ years in a data quality, ML data engineering or applied ML role. * Experience ... Experience with continuous learning or active learning pipelines for production ML systems.

Outpost

Machine Learning Data Engineer

Seattle, WA · On-site

$130 - $160/hr

Qualifications: * 3+ years in a data quality, ML data engineering or applied ML role. * Experience ... Experience with continuous learning or active learning pipelines for production ML systems.

Hudson Manpower

DATA ENGINEER IV

Cincinnati, OH · On-site

$68 - $70/hr

Machine Learning Data Enablement squad in the Data Insights Tribe Required: In office 4 days a week minimum (Monday-Thursday) We're hiring a Data Engineer to join our newly launched Machine Learning ...

Corning

As a Machine Learning Engineer, you will work within a collaborative technical team to build ... You will partner with data scientists, analytics leaders, IT, and manufacturing teams to move ...

KSB GIW, Inc.

Machine Learning Engineer

Grovetown, GA · On-site

$70 - $110/hr

Machine Learning Engineer Department: Engineering, Research & Development Reports to: Metallurgical ... You'll build the data foundation that powers this work, implement and train models that bridge ...

Instant Serve LLC

AI Data Engineer

Moline, IL · On-site

$103K - $124K/yr

Work closely with Data Scientists, AI Engineers, and other stakeholders to ensure data is properly structured for machine learning models and other analytics use cases. Data Quality & Governance:

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Machine Learning Data Engineer information

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How much do machine learning data engineer jobs pay per year?

As of Aug 28, 2026, the average yearly pay for machine learning data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What is a machine learning data engineer?

A Machine Learning Data Engineer is responsible for designing, building, and maintaining the data infrastructure that supports machine learning models. They develop data pipelines, ensure data quality, and optimize data storage for efficient processing. This role involves working with large-scale datasets, implementing ETL processes, and collaborating with data scientists to deploy machine learning models. Strong knowledge of databases, cloud platforms, and programming languages like Python and SQL is essential. Their work enables organizations to leverage machine learning effectively by providing reliable and scalable data solutions.

What are the typical daily responsibilities of a machine learning data engineer?

As a Machine Learning Data Engineer, your daily responsibilities often include designing, building, and maintaining data pipelines that efficiently move and transform data for machine learning applications. You may clean, preprocess, and validate large datasets, optimize storage solutions, and work closely with data scientists to ensure data is accessible and usable for model training and evaluation. Regular collaboration with software engineers and business analysts is common to align project goals and solve data-related challenges. Staying up to date with the latest tools and technologies is also important, as you'll help enable scalable and efficient deployment of machine learning solutions.

What are the key skills and qualifications needed to thrive in the machine learning data engineer position, and why are they important?

To thrive as a Machine Learning Data Engineer, you typically need strong programming skills in Python or Scala, a deep understanding of data structures, algorithms, and machine learning concepts, as well as a degree in computer science or a related field. Experience with big data tools like Spark, Hadoop, and cloud platforms such as AWS or Azure, along with knowledge of data pipelines and ETL processes, is highly valuable; certifications in these areas can be advantageous. Problem-solving ability, attention to detail, and strong communication skills help professionals excel when working with diverse technical teams and stakeholders. These skills ensure data engineers can effectively build reliable, scalable data systems that support the development and deployment of machine learning models.

Can a machine learning data engineer become a machine learning engineer?

A machine learning data engineer can transition to a machine learning engineer role by developing skills in model development, algorithms, and deployment, often requiring knowledge of programming languages like Python and frameworks such as TensorFlow or PyTorch. Gaining experience in building and deploying models, along with understanding machine learning concepts, is essential for this career progression.

What is the salary of machine learning data engineer?

The salary of a machine learning data engineer typically ranges from $90,000 to $150,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in cloud platforms and big data tools may earn higher compensation.
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Machine Learning Data Engineer jobs near you
Infographic showing various Machine Learning Data Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Senior Machine Learning Data Engineer - Cambridge

Cambridge, MA • On-site

Motion Recruitment Partners, LLC
Recruiting and Staffing Services • 1 - 5K employees
Learn more about Motion Recruitment Partners, LLCexternal

$125K - $150K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 26 days ago

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.

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