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Machine Learning Ai Jobs in Massachusetts (NOW HIRING)

Base pay range $130,000.00/yr - $215,000.00/yr Direct message the job poster from Alsym Energy Alsym Energy is seeking a Machine Learning Scientist or Engineer to design, build, and deploy agentic AI ...

The Alexa AI team is looking for a passionate, talented, and inventive Machine Learning Engineer with a strong machine learning background, to build capabilities such as fine tuning, distillation ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... The Logistics AI group is responsible for the intelligence and execution behind Instacart ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... The Logistics AI group is responsible for the intelligence and execution behind Instacart ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... The Logistics AI group is responsible for the intelligence and execution behind Instacart ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... The Logistics AI group is responsible for the intelligence and execution behind Instacart ...

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Showing results 1-20

Machine Learning Ai information

See Massachusetts salary details

$27.8K

$46.5K

$96.1K

How much do machine learning ai jobs pay per year?

As of Aug 8, 2026, the average yearly pay for machine learning ai in Massachusetts is $46,507.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,500.00 and $50,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a machine learning AI?

To thrive as a Machine Learning AI Engineer, you need a strong background in mathematics, statistics, programming (typically Python), and a relevant degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow and PyTorch, as well as cloud platforms and data processing tools, is essential, and certifications in these areas can be advantageous. Strong problem-solving, communication, and collaboration skills help you effectively translate business needs into technical solutions and work well within multidisciplinary teams. These skills ensure you can develop robust AI models that address real-world challenges and deliver meaningful business impact.

What is a machine learning AI?

A Machine Learning AI specialist is a professional who develops algorithms and models that enable computers to learn from and make predictions or decisions based on data. They work with large datasets, train and evaluate machine learning models, and often collaborate with software engineers and data scientists to integrate AI solutions into products and services. Their work is crucial in fields like natural language processing, computer vision, and predictive analytics, helping organizations automate tasks, gain insights, and improve efficiency.

What are some common challenges faced when collaborating with cross-functional teams as a machine learning AI?

As a Machine Learning AI professional, you’ll often collaborate with data engineers, software developers, and product managers. A common challenge is bridging the gap between complex AI models and practical business requirements, ensuring your solutions are both technically sound and aligned with user needs. Effective communication is key, as you’ll need to explain technical concepts to non-technical stakeholders and adapt your models based on feedback. Building trust and fostering a collaborative environment will help ensure successful project outcomes and foster continual learning.

What is the difference between Machine Learning Ai vs Data Scientist?

AspectMachine Learning AiData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; experience with programming and algorithmsDegree in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentDeveloping algorithms, training models, deploying AI systemsAnalyzing data, creating reports, interpreting results
Employer & Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, marketing, tech firms

Machine Learning Ai focuses on developing and deploying AI algorithms and models, while Data Scientists analyze and interpret data to inform business decisions. Both roles often collaborate but have distinct focuses within the data and AI ecosystem.

What cities in Massachusetts are hiring for Machine Learning Ai jobs? Cities in Massachusetts with the most Machine Learning Ai job openings:
Infographic showing various Machine Learning Ai job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $46,507 per year, or $22.4 per hour.

Machine Learning Engineer Hybrid in Burlington, MA

Matrixspace

Burlington, MA • On-site

$165 - $200/hr

Other

Posted 3 days ago

New


Job description

Help us bridge machine learning research and real-world deployment!

MatrixSpace develops AI-enabled radar and sensing systems that help people understand what's happening in the world around them. By combining advanced radar, edge computing, and AI, we deliver situational awareness in environments where traditional sensing solutions struggle.

We're looking for a hands‑on Machine Learning Engineer who enjoys turning cutting‑edge ML research into production‑ready software. You'll partner closely with our Data Scientists, taking new algorithms and implementing them in performant, maintainable, and scalable production systems. You'll also help build the ML infrastructure and tooling that accelerates future research, while ensuring our AI solutions are reliable enough for real‑world deployment.

If you're technically curious, highly collaborative, and motivated by solving complex real‑world problems, we'd love to talk.

What You'll Do
  • Partner with Data Scientists to transform research algorithms into robust, production-quality software.
  • Implement machine learning algorithms in high-performance C++ and Python with a focus on maintainability, scalability, and real-time performance.
  • Build and improve machine learning infrastructure, tooling, and training pipelines that enable faster experimentation and more efficient model development.
  • Design and implement AI agents, agentic workflows, and LLM-powered applications.
  • Deploy and maintain AI workloads across edge, near-edge, and cloud environments.
  • Collaborate across engineering and research teams to transition prototypes into production systems.
What We're Looking For

This position requires working directly or indirectly with the US Government in restricted environments. Candidates must be legally authorized to work in the United States without employer sponsorship and may be required to obtain and maintain a U.S. government security clearance in the future.

This is NOT a fully remote position!

Required
  • BS, MS, or PhD in Computer Science, Electrical Engineering, Applied Mathematics, Machine Learning, AI, Robotics, or a related field.
  • Strong hands‑on programming experience in C++ and Python.
  • 3-5 years of experience developing and deploying machine learning systems in production environments.
  • Experience building AI agents, LLM‑based applications, or intelligent automation systems.
  • Strong problem‑solving skills and ability to work across the full development lifecycle.
  • Excellent written and verbal communication and collaboration skills.
Someone Who Will Thrive in This Role
  • Enjoys solving difficult technical challenges that span algorithms, software, and deployment.
  • Enjoys bridging the gap between research and production, finding practical engineering solutions that make advanced ML usable in real‑world products.
  • Takes ownership and drives projects from concept through production.
  • Continuously explores new AI, ML, and agentic technologies.
  • Works effectively across multidisciplinary teams.
  • Balances research innovation with practical product delivery.
  • Builds side projects, experiments with emerging AI tools, or enjoys hands‑on technical exploration.
Bonus Points
  • Experience with radar, RF sensing, sensor fusion, computer vision, robotics, or autonomous systems.
  • Experience with LangChain, LangGraph, LlamaIndex, AutoGen, Semantic Kernel, or similar frameworks.
  • Experience optimizing models for edge deployment using TensorRT, ONNX, OpenVINO, TVM, or similar tools.
  • Experience with embedded systems, GPUs, NPUs, FPGAs, or hardware acceleration.
  • Familiarity with MLOps, CI/CD, model monitoring, and large‑scale production systems.

At MatrixSpace, Machine Learning Engineering is where advanced AI research becomes real‑world capability. This is an engineering‑heavy ML role focused on productionizing algorithms created by Data Scientists, with some ownership of the ML infrastructure that helps those Data Scientists move faster.

Compensation range: $165,000 - $200,000. Actual position within the range will be determined based on experience level of the candidate.

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