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$44.5K

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

As of Jun 5, 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.

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.

What engineers make $300,000 a year?

Senior machine learning data engineers with extensive experience, advanced skills in data pipelines, cloud platforms, and programming languages like Python or Scala can earn $300,000 or more annually. High compensation often reflects leadership roles, specialized expertise, or work at large tech companies and financial institutions.

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.

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Machine Learning Data Engineer jobs near you
Machine Learning / Data Science Engineer

Machine Learning / Data Science Engineer

CapTech Consulting

Philadelphia, PA • On-site

$115K - $138K/yr

Full-time

Medical, Retirement, PTO

Posted 20 days ago

Job description

Company Description
CapTech is an award-winning consulting firm that collaborates with clients to achieve what's possible through the power of technology. At CapTech, we're passionate about the work we do and the results we achieve for our clients. From the outset, our founders shared a collective passion to create a consultancy centered on strong relationships that would stand the test of time. Today we work alongside clients that include Fortune 100 companies, mid-sized enterprises, and government agencies, a list that spans across the country.
Job Description
CapTech Machine Learning Engineers are responsible for designing and implementing data-driven solutions for our clients, with a specific focus on building and deploying scalable machine learning systems in enterprise environments. CapTech employees enjoy a collaborative environment and have many opportunities to learn from and share knowledge with other CapTech analysts, architects, and our clients.
Specific responsibilities for the Machine Learning Engineer position include:
  • Strategizing with clients, data scientists, engineers, and other members of cross-functional teams to implement end-to-end machine learning solutions and identify new machine learning and data science approaches to meet business needs
  • Deconstructing client needs into data-driven processes/models and analytical measures.
  • Analyzing and transforming large datasets hosted on a variety of enterprise-level data platforms (e.g., AWS, Azure, GCP).
  • Designing, developing, and deploying advanced analytical solutions leveraging client data (e.g., recommender systems, natural language processing, risk scoring).
  • Productionizing ML systems with a focus on optimization and scalability to satisfy clients' requirements.
  • Growing CapTech's Machine Learning and Data Science practices through delivering client presentations, writing proposals, attending various business development events, and leading teams of junior data scientists and engineers.

Qualifications
  • Bachelor's degree or equivalent combination of education and experience.
  • Hands-on experience manipulating and analyzing large (multi-billion record) data sets.
  • Hands-on experience developing data-driven solutions using Python, Scala, or similar languages.
  • Proficiency leveraging SQL, Spark, NoSQL, and/or cloud data processing frameworks in a production setting.
  • Proficiency with containerization (e.g., Docker) and microservices.
  • Proficiency with data warehousing tools/environments such as Snowflake, Databricks, Azure SQL, Amazon RDS
  • Comfort and proficiency in framing data-driven problems from cross-industry business requirements.
  • Experience applying analytical methods across multiple business domains (e.g., customer analytics, marketing, finance, digital channels)
  • Hands-on experience implementing production-scale machine learning systems in one or more domains (i.e., personalization, natural language processing, computer vision).
  • Knowledge of DevOps and automation best practices.
  • Knowledge of statistics and statistical modeling methods.
  • Knowledge of model management and model versioning best practices.
  • Experience working with LLMs (e.g., GPT, Claude, Mistral, etc.) in production setting
  • Experience with prompt engineering, MCP and RAG, and agentic AI architectures
  • Strong understanding of conversational UX and prompt evaluation metrics
  • Experience with agentic frameworks in practice (langchain, n8n, pydantic, etc.)
  • Experience with multi-agent orchestration

Additional Information
We want everyone at CapTech to be able to envision a lasting and rewarding career here, which is why we offer a variety of career paths based on your skills and passions. You decide where and how you want to develop, and we help get you there with customizable career progression and a comprehensive benefits package to support you along the way. Alongside our suite of traditional benefits encompassing generous PTO, health coverage, disability insurance, paid family leave and more, we've launched extended benefits to help meet our employees' needs.
  • CapTech is committed to providing a flexible work environment and helping our employees achieve a work-life balance that suits their individual needs. Employees must be available to work onsite in a client location or a CapTech office as requested. We allow CapTech employees to work remotely when compatible with CapTech and client needs.
  • Learning & Development - Programs offering certification and tuition support, digital on-demand learning courses, mentorship, and skill development paths
  • Modern Health -A mental health and well-being platform that provides 1:1 care, group support sessions, and self-serve resources to support employees and their families through life's ups and downs
  • Carrot Fertility -Inclusive fertility and family-forming coverage for all paths to parenthood - including adoption, surrogacy, fertility treatments, pregnancy, and more - and opportunities for employer-sponsored funds to help pay for care
  • Fringe -A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them - ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more
  • Employee Resource Groups - Employee-led committees that embrace and incorporate diversity and inclusion into our day-to-day operations
  • Philanthropic Partnerships - Opportunities to engage in partnerships and pro-bono projects that support our communities.
  • 401(k) Matching - Generous matching and no vesting period to help you continue to build financial wellness

CapTech is an equal opportunity employer committed to fostering a culture of equality, inclusion and fairness - each foundational to our core values. We strive to create a diverse environment where each employee is encouraged to bring their unique ideas, backgrounds and experiences to the workplace. For more information about our Diversity, Inclusion and Belonging efforts, click HERE. As part of this commitment, CapTech will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Laura Massa directly via email lmassa@captechconsulting.com.
At this time, CapTech cannot transfer nor sponsor a work visa for this position. Applicants must be authorized to work directly for any employer in the United States without visa sponsorship.

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