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Machine Learning Engineer Jobs in Groton, CT (NOW HIRING)

GDIT

Machinist

Pawcatuck, CT

$20.24 - $26.45/hr

Will set up and machine many different types of parts to blueprint. Knowledge of G-Code programming ... AI-powered career tool that identifies career steps and learning opportunities Support: An internal ...

Harris

(Remote) Technical Engineer

Carolina, RI · On-site +1

This is a role for engineers who enjoy asking "why," digging into complex problems, and continuously learning. This remote role welcomes candidates anywhere in the US. Preference will be given to ...

Ocean House Collection

Engineer

Westerly, RI · On-site

$21 - $26/hr

Ocean House Management Shift Engineer Ocean House Management Shift Engineer A Collection Unlike Any ... The worker is required to have visual acuity to perform an activity such as: operating machines ...

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Showing results 21-40

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Groton, CT

Machine Learning Engineer information

See Groton, CT salary details

$31.3K

$128K

$192.4K

How much do machine learning engineer jobs pay per year?

As of Aug 14, 2026, the average yearly pay for machine learning engineer in Groton, CT is $128,044.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,900.00 and $154,100.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs

What are the most commonly searched types of Machine Learning Engineer jobs in Groton, CT?

The most popular types of Machine Learning Engineer jobs in Groton, CT are:

What are popular job titles related to Machine Learning Engineer jobs in Groton, CT?

For Machine Learning Engineer jobs in Groton, CT, the most frequently searched job titles are:

What cities near Groton, CT are hiring for Machine Learning Engineer jobs?

Cities near Groton, CT with the most Machine Learning Engineer job openings:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Groton, CT as of August 2026, with employment types broken down into 78% Full Time, and 22% Contract. Highlights an 100% In-person job distribution, with an average salary of $128,044 per year, or $61.6 per hour.

D425 Artificial Intelligence (AI) Program Representative

General Dynamics Electric Boat

Groton, CT • On-site

Full-time

Posted 10 days ago

General Dynamics Electric Boat rating

8.3

Company rating: 8.3 out of 10

Based on 164 frontline employees who took The Breakroom Quiz

67th of 539 rated manufacturers

Job description

Position Summary:

Electric Boat is seeking a self-starter who is highly organized, energized by new technology, and motivated by coordinating meaningful, cross-functional work. As an AI Program Representative, you won’t just administer our AI governance process; you’ll help scale it, strengthen it, and evolve it so the company can safely and effectively expand its use of artificial intelligence. You’ll partner closely with the AI Working Group, engineering teams, business functions, IT, and leadership to ensure that our AI initiatives are well structured, responsibly implemented, and aligned with enterprise strategies. If you enjoy coordinating multiple stakeholders, project management, building organizational processes, and working with emerging technologies, this role offers a unique opportunity to help shape the future of AI at Electric Boat. This role will support Groton Shipyard, New London and Quonset Point locations and require local travel. 

Responsibilities: 

The AI Program Representative will serve as the centralized point of contact and lead for a new AI Center of Excellence. Responsibilities include: 

Scale and Strengthen AI Governance 

  • Lead day-to-day execution of EB’s AI governance process, including intake, evaluation, prioritization, and risk assessment of potential AI use cases. 
  • Identify gaps, inefficiencies, and bottlenecks and drive improvements that allow the governance process to scale effectively as AI adoption grows. 
  • Maintain and expand governance materials including AI MDDs, risk evaluation templates, workflows, and guidance documents. 
  • Promote responsible AI practices and ensure alignment with cybersecurity, data governance, and corporate policy. 

Coordinate Projects and Keep Work Moving 

  • Manage a growing portfolio of AI projects across shipyard, shipboard, design & engineering, and business operations domains. 
  • Work with teams to define scope, understand data and technology requirements, and identify risks early. 
  • Track schedules, budgets, milestones, and deliver consistent monthly updates to leadership. 
  • Support resourcing by coordinating internal staffing and collaborating with external partners when applicable. 

Connect Teams and Build Organizational Momentum 

  • Serve as the central point of contact for AI-related coordination across EB. 
  • Facilitate communication among engineering, design, IT, operations, and business functions to maintain alignment and clarity. 
  • Support workforce development through mentoring, guidance, and helping integrate AI literacy into training conversations. 

Drive Growth, Innovation, and Continuous Improvement 

  • Help the company identify infrastructure, tooling, training, and process needs to support wider AI adoption. 
  • Drive improvements to workflows, communication channels, evaluation criteria, and documentation that enable smoother scaling of AI initiatives. 
  • Support departmental and enterprise-level improvement initiatives linked to responsible and effective AI adoption. 

Required:

  • Bachelor's degree in Engineering, Project Management or Business.
  • Minimum 5 years' of experience in engineering, data science, project management, software, or other technical coordination roles.
  • Ability to obtain and maintain a Secret Security clearance through the Department of Defense

Preferred:

  • 7+ years of experience at Electric Boat.
  • Experience with artificial intelligence, machine learning, data analysis, or related technologies. 
  • Experience leading projects or coordinating cross-functional efforts. 
  • Familiarity with EB engineering workflows, submarine design, or shipyard operations. 
  • Experience contributing to or developing governance frameworks or repeatable business processes.

  • Proven ability to work independently and take initiative to solve problems with limited oversight. 
  • Strong organizational, planning, and coordination skills. 
  • Excellent communication skills suited for both technical and non-technical audiences. 
  • Proficiency with MS Office tools. 
  • Ability to manage multiple evolving priorities in a fast-paced environment.

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