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Data Engineer Ml Jobs (NOW HIRING)

Software Engineer, ML Data

San Francisco, CA · On-site

$180K - $230K/yr

  • Medical

  • Dental

  • Vision

As a Software Engineer on the Machine Learning Data Platform team at Liftoff, you will: * Work with an experienced team of ML, Software, and Infrastructure Engineers that are building the ML platform ...

Data Engineer 3

Atlanta, GA · On-site

$110K - $132K/yr

Partner with data engineers, ML engineers, and product teams to improve data and model quality * Support continuous improvement of QA processes and software development lifecycle * Document test ...

Data Engineer

El Segundo, CA · On-site

$122K - $146K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

About the Role As a Data Engineer at Circadia Health, you will play a critical role in building and ... Reporting directly to the CTO, you will work closely with backend engineers, ML engineers, clinical ...

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Data Engineer Ml information

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$46K

$165K

$243.5K

How much do data engineer ml jobs pay per year?

As of Aug 19, 2026, the average yearly pay for data engineer ml in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What does a data engineer ML do?

A Data Engineer ML (Machine Learning) is responsible for designing, building, and maintaining the data pipelines and infrastructure necessary for machine learning applications. They clean, process, and organize large datasets to ensure data quality and accessibility for data scientists and ML engineers. In addition, they may work on deploying machine learning models to production environments and optimizing data workflows for efficiency and scalability.

What are the key skills and qualifications needed to thrive as a data engineer ML?

To thrive as a Data Engineer ML, you need strong programming skills (especially in Python or Scala), knowledge of data modeling, and a solid foundation in database technologies, typically supported by a degree in computer science or a related field. Familiarity with big data frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and ETL tools, as well as relevant certifications, is highly beneficial. Excellent problem-solving abilities, teamwork, and clear communication help you collaborate with data scientists and stakeholders effectively. These skills are essential for building robust data pipelines and infrastructure that enable scalable, high-quality machine learning solutions.

How do data engineer ML roles typically collaborate with data scientists and machine learning engineers on projects?

Data Engineer ML professionals work closely with data scientists and machine learning engineers by building and maintaining robust data pipelines, ensuring clean and reliable datasets are readily available for modeling and analysis. They often participate in meetings to understand model requirements, help optimize data storage for performance, and support the deployment of machine learning models into production environments. Effective collaboration involves continuous communication to troubleshoot data issues, implement data validation, and scale solutions as project needs evolve. This teamwork ensures that data-driven projects move efficiently from experimentation to deployment.

What is the difference between Data Engineer Ml vs Data Scientist?

AspectData Engineer MlData Scientist
Required CredentialsBachelor's in CS, Data Engineering certificationsBachelor's/Master's in CS, Data Science certifications
Work EnvironmentBuilding data pipelines, managing databasesAnalyzing data, creating models
Employer & Industry UsageTech companies, finance, healthcareResearch institutions, tech firms, finance

Data Engineer Ml focuses on developing and maintaining data infrastructure and pipelines, while Data Scientists analyze data and build predictive models. Both roles often collaborate but serve different functions within data teams.

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What cities are hiring for Data Engineer Ml jobs?

Cities with the most Data Engineer Ml job openings:

What states have the most Data Engineer Ml jobs?

States with the most job openings for Data Engineer Ml jobs include:

Infographic showing various Data Engineer Ml 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 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Senior/Staff Software Engineer, ML Data

Icehouseventures

Mountain View, CA • On-site

$193.93 - $352.29/hr

Other

Posted yesterday

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Job description

Who We Are

Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale, empowering a safer, richer, and more connected future.

About the Role

We are looking for a Senior/Staff Software Engineer to serve as a technical leader for Nuro’s ML Data engine. You will sit at the critical intersection of Autonomy, Machine Learning, and Infrastructure, acting as an architect for the systems that feed our autonomy AI models.

In this role you will be a member of the Autonomy team responsible for executing the technical strategy for transforming massive amounts of autonomy data into high-value training signals for autonomy decision making. You will design and build data products for autonomy researchers, develop queries for rare "needle-in-a-haystack" scenarios, and trigger labeling and data ingestion workflows without human intervention. You will partner directly with Autonomy ML researchers to understand their data needs, collaborate with infrastructure teams to define the right data interfaces and APIs, and build robust data selection, simulation, and introspection tools that can process data at scale. If you love solving challenging new problems with a mindset of deriving practical solutions to be used in the physical world, come join us

About the Work
  • Data Pipeline Architecture: Design and build scalable data ingestion and processing pipelines that turn data streams into targeted training datasets. Lead initiatives to improve data quality, detect anomalies, and manage out-of-distribution examples to ensure robust model training and deployment.
  • Cross Functional Leadership: Work across autonomy teams and data infra teams to build effective ML data pipelines and products for ML engineers.
  • ML Tooling & Introspection: Develop infrastructure and visualization tools that allow ML researchers to easily introspect data, identify model failure modes, query for new data samples, and understand data distribution shifts.
  • Labeling Operations Integration: Collaborate closely with the data operations team to define quality standards, automate quality control (QC), and streamline the feedback loop between model performance and annotation guidelines.
  • Active Learning & Data Mining Engines: Lead the engineering effort to operationalize research-grade active learning methods. E.g. build systems that compute embeddings or run inference at scale, manage vector databases, and automatically sample the most informative data points for labeling.
About You Required Qualifications
  • 7+ years of experience with a proven track record of technical leadership architecting and delivering complex, multi-system ML data engineering data systems.
  • Education: B.S./M.S. in Computer Science, Artificial Intelligence, Electrical Engineering, Robotics, or equivalent practical experience.
  • Understanding of end-to-end ML data pipelines and their interaction with model training and evaluation.
  • Strong proficiency in C++ and Python, with petabyte-level data management experience.
  • Experience taking data concepts (e.g., "uncertainty sampling") and turning them into stable, 24/7 production services.
Preferred Qualifications
  • Prior experience working in large companies with productionized AI systems working on data engines for large scale machine learning.
  • Experience in workflow orchestration, introspection UI/UX for data understanding, and ML frameworks for foundation model training.
  • Expertise in data-centric AI topics (active learning, pre-training) and their application in autonomous systems.
  • You have subject matter expertise and research in one or more of the following areas: Machine Learning, Deep Learning, Robotics, and have some familiarity with the state of the art in ML for autonomous driving and data utilization.

At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $193,930 and $352,290 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.

At Nuro, we celebrate differences and are committed to a diverse workplace that f...

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