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Mlops Data Engineer Jobs in Boston, MA (NOW HIRING)

NxT Level

Lead Engineer, MLOps

Boston, MA · On-site

$111K - $146K/yr

MLOps, ML Platform, Data Science Infrastructure, AI-Assisted Development, Supply Chain Technology ... Lead and grow a team of engineers across ML infrastructure, MLOps, and embedded data science ...

NxT Level

Lead Engineer, MLOps

Boston, MA · On-site

$111K - $146K/yr

MLOps, ML Platform, Data Science Infrastructure, AI-Assisted Development, Supply Chain Technology ... Lead and grow a team of engineers across ML infrastructure, MLOps, and embedded data science ...

NxT Level

Lead Engineer, MLOps

Boston, MA · On-site

$111K - $146K/yr

MLOps, ML Platform, Data Science Infrastructure, AI-Assisted Development, Supply Chain Technology ... Lead and grow a team of engineers across ML infrastructure, MLOps, and embedded data science ...

NxT Level

Lead Engineer, MLOps

Boston, MA · On-site

$111K - $146K/yr

MLOps, ML Platform, Data Science Infrastructure, AI-Assisted Development, Supply Chain Technology ... Lead and grow a team of engineers across ML infrastructure, MLOps, and embedded data science ...

aPriori Technologies Inc

Senior Data Engineer

Concord, MA · On-site

$116K - $157K/yr

Experience with traditional AI/ML/MLOps or GenAI, LLMOps Education and Experience: * Bachelor's or Master's degree in Computer Science, Engineering, or a related field. * 5+ years' experience in data ...

Merck KgaA

Senior Data & ML Ops Engineer

Boston, MA · On-site

$137K - $206K/yr

As a Senior Data & MLOps Engineer, you own the data and MLOps foundations - from ingestion to production - collaborating with Data Science, Commercial, Medical, Analytics, and IT to turn prototypes ...

Hatch IT

Senior Data Engineer

Somerville, MA · On-site

$115K - $157K/yr

As a Senior Data Engineer at VIA, you will play a pivotal role in the growth of their solutions ... Support AI operations (MLOps) by managing versioning, containerization, and deployment of AI models

Hatch IT

Senior Data Engineer

Somerville, MA

$115K - $157K/yr

As a Senior Data Engineer at VIA, you will play a pivotal role in the growth of their solutions ... Support AI operations (MLOps) by managing versioning, containerization, and deployment of AI models

Hatch IT

Senior Data Engineer

Somerville, MA

$120K - $160K/yr

As a Senior Data Engineer at VIA, you will play a pivotal role in the growth of their solutions ... Support AI operations (MLOps) by managing versioning, containerization, and deployment of AI models

Zeitview

Senior MLOps Engineer I

Boston, MA · On-site +1

$113K - $155K/yr

As the Senior MLOps Engineer I, you will help turn the models built by our ML Scientists, Data Scientists, and Perception Engineers into reliable, production-grade services. You'll work on the ...

Accenture

Google Senior Data Engineer

Boston, MA · On-site

$94K - $266K/yr

Implement ML pipelines and help establish MLOps processes (monitoring, retraining, deployment ... Collaborate closely with senior data engineers, ML engineers, and architects. * Contribute to ...

Zeitview

Senior MLOps Engineer I

Boston, MA · On-site

$113K - $155K/yr

As the Senior MLOps Engineer I, you will help turn the models built by our ML Scientists, Data Scientists, and Perception Engineers into reliable, production-grade services. You'll work on the ...

WHOOP

Senior AI Researcher (Foundation AI)

Boston, MA · On-site

... MLOps, data engineering, and software engineering teams to operationalize models for production deployment, ensuring robustness, reproducibility, and observability. • Partner with product and ...

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Showing results 1-20

All JobsMlops Data Engineer JobsMlops Data Engineer Jobs in Boston, MA

Mlops Data Engineer information

See Boston, MA salary details

$48.3K

$140.9K

$192.8K

How much do mlops data engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for mlops data engineer in Boston, MA is $140,924.00, according to ZipRecruiter salary data. Most workers in this role earn between $124,400.00 and $149,400.00 per year, depending on experience, location, and employer.

What is an MLOps data engineer?

MLOps Data Engineers are professionals who blend expertise in machine learning (ML), operations (Ops), and data engineering to streamline the deployment and management of ML models in production environments. They design and maintain data pipelines, automate workflows, and ensure the scalability, reliability, and reproducibility of machine learning systems. Their role bridges the gap between data scientists and IT operations, enabling seamless integration of ML models into real-world applications.

What are the key skills and qualifications needed to thrive as an MLOps data engineer?

To thrive as an MLOps Data Engineer, you need a strong background in data engineering, machine learning workflows, and software development, usually supported by a degree in computer science or a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), CI/CD pipelines, containerization tools (like Docker and Kubernetes), and familiarity with orchestration frameworks are typically required, along with certifications in cloud or data engineering. Strong problem-solving abilities, collaboration, and clear communication set professionals apart in this role. These skills and qualities are critical to efficiently deploying scalable machine learning solutions and ensuring smooth collaboration between data science and engineering teams.

What are some common challenges MLOps data engineers face when deploying machine learning models into production?

MLOps Data Engineers often encounter challenges such as ensuring seamless integration between data pipelines and model serving infrastructure, managing consistent data quality, and automating model retraining and monitoring. Another common hurdle is maintaining scalability and reliability as data volumes grow, and efficiently collaborating with data scientists, software engineers, and DevOps teams. Addressing these challenges requires strong communication skills, familiarity with cloud platforms, and a proactive approach to troubleshooting and automation.

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

AspectMlops Data EngineerData Scientist
Required SkillsMachine learning deployment, cloud platforms, scripting, data pipelinesStatistical analysis, programming, data visualization, machine learning modeling
CertificationsCloud certifications, ML engineering coursesData science certifications, statistical courses
Work EnvironmentData pipelines, cloud infrastructure, ML deployment systemsData analysis, modeling, research environments
Industry UsageTech companies, AI-focused firms, cloud service providersResearch institutions, analytics firms, tech companies

The main difference between an Mlops Data Engineer and a Data Scientist lies in their focus areas. Mlops Data Engineers specialize in deploying, maintaining, and scaling machine learning models within production environments, emphasizing infrastructure and automation. Data Scientists primarily focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but their day-to-day tasks and career paths differ significantly.

Are MLOps Data Engineers in demand?

MLOps Data Engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are skilled in deploying, managing, and maintaining ML models using tools like Docker, Kubernetes, and cloud platforms, making their expertise highly sought after in data-driven organizations.

Is MLOps required for data engineers?

MLOps is increasingly important for data engineers involved in deploying and maintaining machine learning models, as it encompasses practices like automation, monitoring, and version control. While not always mandatory, knowledge of MLOps tools such as Docker, Kubernetes, and CI/CD pipelines enhances a data engineer's ability to support scalable and reliable ML systems.

What are popular job titles related to Mlops Data Engineer jobs in Boston, MA?

For Mlops Data Engineer jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Mlops Data Engineer jobs in Boston, MA look for?

The top searched job categories for Mlops Data Engineer jobs in Boston, MA are:

What cities near Boston, MA are hiring for Mlops Data Engineer jobs?

Cities near Boston, MA with the most Mlops Data Engineer job openings:

Mlops Data Engineer jobs near you
Infographic showing various Mlops Data Engineer job openings in Boston, MA as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 15% Part Time, 2% Temporary, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $140,924 per year, or $67.8 per hour.

Lead Engineer, MLOps

NxT Level

Boston, MA • On-site

$111K - $146K/yr

Other

Posted 27 days ago

Job description

Technical Lead Manager, Machine Learning Operations
Location: United States
Employment Type: Full-time
Focus: MLOps, ML Platform, Data Science Infrastructure, AI-Assisted Development, Supply Chain Technology
About Our Client
Our client is building modern logistics infrastructure for the future of ecommerce.
Their platform helps brands and consumers create a better post-purchase experience by making shopping, shipping, delivery, and returns more seamless. By combining next-generation technology with a vertically integrated logistics network, our client gives ecommerce brands more control over the customer delivery experience and helps turn delivery into an extension of the brand.
The company supports millions of deliveries and partners with some of the most recognized consumer brands in the market. Their culture is high-performance, merit-based, and built for people who want to compete, win, make an impact, and help build an enduring company.
About the Role
Our client is hiring a Technical Lead Manager, Machine Learning Operations to own the Data Science platform and lead the roadmap for building a more sophisticated, stable, and scalable ML infrastructure foundation.
This person will lead a team focused on ML infrastructure, ML operations, and embedded data science engineering. The team partners closely with data scientists to ensure forecasting, network orchestration, pricing, routing, and other machine learning systems are well-designed, production-ready, and built to scale.
This is a hands-on leadership role. You'll manage and grow the team while still contributing technically through architecture, code, design reviews, roadmap ownership, and setting the engineering bar.
What You'll Do
  • Lead and grow a team of engineers across ML infrastructure, MLOps, and embedded data science project work
  • Own the 1-2 year roadmap for improving the company's ML platform and operations research infrastructure
  • Standardize and improve training infrastructure, serving infrastructure, deployment pipelines, monitoring, permissions, environments, and service operations
  • Embed engineers into major science initiatives across forecasting, network orchestration, pricing, routing, and supply chain optimization
  • Help ensure data science projects are production-ready from day one
  • Build templates, patterns, and platform standards that help new ML systems get up and running quickly
  • Partner closely with data science, engineering, developer experience, and platform teams
  • Drive adoption of AI-assisted and agentic development workflows across the Data Science organization
  • Set standards for using AI in EDA, model iteration, ML/OR methodology, and development velocity
  • Review designs, write code, improve technical quality, and raise the bar for production ML systems
  • Participate in the on-call rotation for production data science systems

What We're Looking For
  • Bachelor's degree with 6+ years of Machine Learning Engineering experience, or Master's degree with 4+ years of Machine Learning Engineering experience
  • Experience leading or managing high-velocity ML platform, MLOps, or ML infrastructure teams
  • Strong hands-on experience building production ML systems
  • Experience with ML platforms, including training infrastructure, serving infrastructure, feature stores, orchestration, monitoring, and deployment pipelines
  • Strong Python experience
  • Experience driving AI-assisted or agentic tooling adoption inside an engineering or data science organization
  • Strong knowledge of cloud-based data engineering and data science tools, preferably AWS
  • Experience with data warehouses such as Redshift, Databricks, Snowflake, or similar platforms
  • Experience with open-source large-scale ML tooling such as Ray, Flink, Feast, or similar technologies
  • Ability to balance short-term business impact with long-term platform vision
  • Strong communication skills and a business-value-first approach to technical work

Bonus Experience
  • Experience building ML systems in logistics, ecommerce, supply chain, transportation, marketplaces, or operations-heavy businesses
  • Experience supporting forecasting, routing, pricing, network optimization, or operations research systems
  • Experience partnering directly with data science teams to productionize models
  • Experience building reusable ML templates, internal platforms, or service creation frameworks
  • Experience improving developer experience or AI-assisted development workflows

Why This Opportunity
  • Lead the platform foundation behind high-impact data science systems
  • Work on machine learning problems tied directly to real-world logistics, delivery, pricing, forecasting, and network orchestration
  • Manage and grow a technical team while staying hands-on
  • Own a meaningful roadmap for ML infrastructure at scale
  • Help drive AI-assisted development adoption across a data science organization
  • Build systems that power millions of package decisions and help major ecommerce brands deliver better customer experiences
  • Join a high-performance team with strong growth potential and meaningful equity upside

Apply