1

Data Engineer Ml Jobs (NOW HIRING)

Data Engineer

Manhattan, NY · On-site +1

$126.20K - $151.60K/yr

Collaborate with ML engineers, data scientists, and software developers to deliver reliable, reusable, and versioned feature sets. * Implement CI/CD pipelines, testing frameworks, and observability ...

Data Engineer

Manhattan, NY · On-site

$126.10K - $151.40K/yr

Collaborate with ML engineers, data scientists, and software developers to deliver reliable, reusable, and versioned feature sets. * Implement CI/CD pipelines, testing frameworks, and observability ...

Sr. Data Engineer with ML

New York, NY · On-site

$125.30K - $150.40K/yr

Collaborate with data scientists and ML engineers to streamline workflows and ensure scalable, reliable model deployment. * Configure MLflow servers and APIs to connect securely and efficiently with ...

Data Engineer

Los Angeles, CA

$123.40K - $148.20K/yr

Reporting directly to the Lead AI Engineer, you will work closely with backend engineers, ML ... What You'll Do Data Pipeline & Integration Development * Design, build, and maintain scalable data ...

Data Engineer

Los Angeles, CA · On-site

$123.40K - $148.20K/yr

Reporting directly to the Lead AI Engineer, you will work closely with backend engineers, ML ... What You'll Do Data Pipeline & Integration Development * Design, build, and maintain scalable data ...

Data Engineer - AI/ML

Tampa, FL · Hybrid

$108.20K - $129.90K/yr

We are seeking a Data Engineer with strong AI/ML expertise to modernize and scale our Business Intelligence (BI) capabilities. This role will design and build data pipelines, deploy machine learning ...

Software Engineer, ML Data Infrastructure

Mountain View, CA · On-site

$136.30K - $163.60K/yr

They are seeking a Software Engineer for their ML Data Infrastructure team to design and develop scalable data pipelines and systems that support the evaluation and performance of autonomous driving ...

Data Engineer

Los Angeles, CA · On-site

$123.40K - $148.20K/yr

Reporting directly to the Lead AI Engineer, you will work closely with backend engineers, ML ... What You'll Do Data Pipeline & Integration Development * Design, build, and maintain scalable data ...

Job Title: Sr. ML Engineer / ML Architect Location-Type: Remote Start Date Is: June 16 Duration ... Build a more scalable and configurable data product * Improve optimization performance and compute ...

New

Data Engineer

Manhattan, NY · On-site

$126.20K - $151.60K/yr

Job Title- Data Engineer Location- New York, NY 10112 Reporting Type- Onsite Duration: 10 months Summary This role involves building and delivering advanced data science and AI/ML solutions in an ...

Erwartungsmanagement Anforderungen Mehrjahrige Erfahrung als MLOps Engineer, ML Engineer oder Data ... Engineer Sehr gute Kenntnisse in Kubernetes-/OpenShift-basierten Umgebungen Erfahrung mit ML ...

$102.10K - $122.70K/yr

... for ML models Enable data availability for training, validation, and inference workflows Understand and apply key ML concepts (supervised/unsupervised learning, model evaluation, bias/variance ...

Senior Data Engineer

Edmond, OK · Remote

$95.80K - $130.10K/yr

Enable ML & LLM Use Cases: Prepare and curate datasets suitable for predictive modeling ... Stay current on data engineering, ML, and LLM-related tools, patterns, and best practices. What It ...

Senior Data Engineer

Edmond, OK · On-site

$95.80K - $130.10K/yr

Enable ML & LLM Use Cases: Prepare and curate datasets suitable for predictive modeling ... Stay current on data engineering, ML, and LLM-related tools, patterns, and best practices. What It ...

next page

Showing results 1-20

Data Engineer Ml information

See salary details

$46K

$165K

$243.5K

How much do data engineer ml jobs pay per year?

As of May 30, 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 are the key skills and qualifications needed to thrive as a Data Engineer ML, and why are they important?

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 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 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.

More about Data Engineer Ml jobs
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 May 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Data Engineer

Munich RE

Manhattan, NY • On-site, Remote

$126.20K - $151.60K/yr

Other

Medical, Dental, Life, Retirement, PTO

Posted 28 days ago


Job description

We're adding to our diverse team of experts and are looking to hire those who are committed to building a culture that enables the creation of innovative solutions for our business units and clients. We will consider a range of experience for this role and the offer will be commensurate with that.

The Company

As a member of Munich Re's US operations, we offer the financial strength and stability that comes with being part of the world's preeminent insurance and reinsurance brand. Our risk experts work together to assemble the right mix of products and services to help our clients stay competitive - from traditional reinsurance coverages, to niche and specialty reinsurance and insurance products.

Job Overview:

We are seeking a highly skilled Senior Data Engineer - DBX Platform (ML & Feature Engineering Focus) with a strong software engineering background to join our AI/ML Engineering GSI IT Team. In this role, you will be focused on building a DBX-based data platform that powers machine learning and advanced analytics. This role is ideal for someone who thrives at the intersection of data engineering, ML infrastructure, and software development, and is passionate about enabling scalable, production-grade feature engineering pipelines.

Key Responsibilities:

    • Build and optimize DBX ETL/ELT pipelines for feature extraction, transformation, and loading from structured and unstructured data sources.
    • Collaborate with ML engineers, data scientists, and software developers to deliver reliable, reusable, and versioned feature sets.
    • Implement CI/CD pipelines, testing frameworks, and observability for data workflows.
    • Develop feature stores, metadata tracking, and lineage tools to support data Ops.
    • Ensure data quality, governance, and compliance across all data assets.
    • Optimize performance and cost-efficiency of DBX clusters and jobs for data workloads.
    • Contribute to the architecture and design of the data platform and feature engineering framework.

Qualifications:

    • Strong proficiency in Python and relevant scripting languages, with experience in software development and scripting for DBX.
    • Expertise with libraries and frameworks (e.g., Pandas, Numpy, Scikit-Learn, TensorFlow, PyTorch, DBX, MLFlow, dvc, dbt) and the ability to select the right tools for the use case.
    • Experience building inference endpoints (APIs) and managing compute architecture for efficient model inference and data handling.
    • Very good Azure and data & AI technology skills - specifically: DBX/ Python, Azure DBX Store, Azure AI Search.
    • Experience with DevOps practices, including Git, CI/CD using tools such as Azure Pipelines, or similar.
    • Several years of experience in machine learning, data science, or a related field, with a strong understanding of statistics and data analysis.
    • Experience with Azure especially with data and ML services, containerization (Docker.

Preferred Qualifications:

    • Advanced Degree: Master's degree in Computer Science, Engineering, Mathematics, with 5+ years of ML implementation experience or Ph.D. with 2+ years of hands-on ML Project experience.
    • Experience with Big Data: Strong proficiency with big data technologies such as Azure DBX and Spark.
    • Leadership Experience: Previous experience leading a team of data scientists or engineers.

Benefits:

    • Competitive employee benefits, including comprehensive health insurance, dental and sports coverage, and opportunities for certified training.
    • Flexibility in work arrangements, including home office options and flexible working hours.
    • A positive, team-oriented environment that fosters mutual trust, creativity, and initiative.
    • Opportunities for career growth within a global, innovative framework.
    • A diverse, multicultural workplace with a strong emphasis on team collaboration and professional development.

At Munich Re US, we see Diversity and Inclusion as a solution to the challenges and opportunities all around us. Our goal is to foster an inclusive culture and build a workforce that reflects the customers we serve and the communities in which we live and work. We strive to provide a workplace where all of our colleagues feel respected, valued and empowered to achieve their very best every day. We recruit and develop talent with a focus on providing our customers the most innovative products and services.

We are an equal opportunity employer. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

The Company is open to considering candidates in Princeton, NJ. The salary range posted below applies to the Company's Princeton location.

The base salary range anticipated for this position is $104,200 - $152,800 plus opportunity for company bonus based upon a percentage of eligible pay. In addition, the company makes available a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, 401k match, retirement savings plan, paid holidays and paid time off (PTO).

The salary estimate displayed represents the typical salary range for candidates hired in this position in Princeton. Factors that may be used to determine your actual salary include your specific skills, how many years of experience you have and comparison to other employees already in this role. Most candidates will start in the bottom half of the range.

Apply Now