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Machine Learning Data Engineer information

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$44.5K

$129.7K

$177.5K

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

As of Jul 17, 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 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 data engineer become a machine learning engineer?

A data engineer can transition to a machine learning engineer role by gaining knowledge of machine learning algorithms, model development, and deployment techniques. Skills in programming languages like Python, experience with frameworks such as TensorFlow or PyTorch, and understanding of data pipelines are essential for this progression.

What is a Machine Learning Data Engineer job?

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.

Will MLE be replaced by AI?

Machine Learning Data Engineers (MLEs) design, build, and maintain data pipelines and models that AI systems rely on. While AI automation tools can handle some tasks, MLE skills in data engineering, programming, and system architecture remain essential for developing and managing AI infrastructure effectively. The role is expected to evolve with advancements in AI, but it is unlikely to be fully replaced in the near future.

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 engineers make $500,000?

Senior machine learning data engineers with extensive experience, advanced skills in data architecture, and proficiency in tools like Spark and cloud platforms can earn $500,000 or more annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of technical expertise, leadership responsibilities, and industry reputation.

What is a $900000 AI job?

A $900,000 AI-related job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data modeling, and experience with tools like TensorFlow or PyTorch. These positions usually involve leadership responsibilities, strategic planning, and may require multiple years of specialized experience or advanced degrees. Compensation at this level reflects the value of expertise in developing and deploying complex AI systems in competitive industries.
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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 July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Director, AI / Machine Learning Data Engineer

BNY

Lake Mary, FL

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 27 days ago

Job description

We're seeking a future team member for the role of Director, AI / Machine Learning Engineer to join our AI Hub team. This role is located in Lake Mary, FL.

This role is located in our AI Hub and is focused on building AI-powered tools and platforms that improve the way engineers design, build, test, and operate software. This is a highly visible leadership opportunity for a hands-on technical leader who can combine deep applied AI expertise with strong software engineering judgment to deliver practical, scalable solutions in an enterprise environment while leading and developing a high-performing engineering team.

In this role, you'll make an impact in the following ways:

  • Lead the design, development, and delivery of applied AI solutions hands-on, providing technical direction and execution leadership for machine learning and artificial intelligence products.

  • Bring deep knowledge of Applied AI, LLMs, fine tuning, model evaluation, and approaches to building fit-for-purpose models, copilots, and agents for engineering use cases.

  • Drive technical discovery, prototyping, and experimentation to evaluate tools, frameworks, and model approaches, translating findings into practical recommendations and scalable implementation plans.

  • Partner closely with engineering and business stakeholders to understand roadmaps, pain points, and workflows, and define success measures that demonstrate developer, engineering, and business impact.

  • Lead and manage a team of AI / machine learning engineers, supporting performance, coaching and development, and creating a strong culture of technical excellence, accountability, and collaboration.

  • Bring expertise in applying AI to improve the software development lifecycle and empower builders, designers, and developers through trusted, secure, and production-grade capabilities.

  • Contribute to the achievement of Application Development objectives by establishing strong practices across architecture, delivery, reliability, and responsible AI adoption.

To be successful in this role, we're seeking the following:

  • Bachelor's degree in computer science engineering or a related discipline, or equivalent work experience required; advanced degree is beneficial. 

  • 12+ years of experience in software development required; experience in the securities or financial services industry is a plus.  

  • Advanced experience, preferably 10+ years, in applied AI/ML, model development, and software engineering, including experience deploying solutions into production environments.

  • Demonstrated experience managing technical teams, mentoring engineers, and balancing people leadership with hands-on technical direction and delivery ownership.

  • Ability to lead as a hands-on technical leader, collaborating with, mentoring, and guiding engineers while driving architecture, implementation, and delivery decisions.

  • Strong understanding of enterprise software practices, MLOps / LLMOps, evaluation frameworks, and how to create secure, scalable, and sustainable AI architectures.

  • Ability to communicate technical ideas clearly and influence a range of audiences, including engineers, product partners, and senior business stakeholders.

At BNY, our culture allows us to run our company better and enables employees' growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world's investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.

Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance - and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary.

At BNY, our culture speaks for itself, check out the latest BNY news at BNY Newsroom & BNY LinkedIn

 Here's a few of our recent awards:

  • America's Most Innovative Companies, Fortune, 2025
  • World's Most Admired Companies, Fortune 2025
  • "Most Just Companies", Just Capital and CNBC, 2025

    Our Benefits and Rewards:

    BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life's journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter.

    BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.

    BNY assesses market data to ensure a competitive compensation package for our employees. The expected base salary for this position when employment commences can be found in the Job Info section at the bottom of the posting. 

    Base salary offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Base salary is only part of the total rewards package, which may include eligibility for an annual discretionary incentive award. Subject to the terms and conditions of the applicable plans then in effect, eligible employees may enroll in a 401(k) plan as well as participate in Company-sponsored medical, dental, vision, and basic life insurance plans for the employee and the employee's eligible dependents. Eligible employees also may receive other benefits (including various paid time off benefits, such as vacation and sick time), dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

    If hired, the employee will be in an "at will" position and the Company reserves the right to modify base salary (as well as any other discretionary payments or compensation programs) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

    Apply