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

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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 Jul 23, 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 engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

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 engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

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.

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 cities near Groton, CT are hiring for Machine Learning Engineer jobs? Cities near Groton, CT with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Groton, CT as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, and 3% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $128,044 per year, or $61.6 per hour.
GENERAL ENGINEER/ARCHITECT (CONSTRUCTION ENGINEER)

GENERAL ENGINEER/ARCHITECT (CONSTRUCTION ENGINEER)

U.S. Department of Defense (DOD)

Groton, CT • On-site

$100K/yr

Other

Posted 6 days ago


U.S. Department Of Defense rating

7.8

Company rating: 7.8 out of 10

Based on 535 frontline employees who took The Breakroom Quiz

25th of 45 rated military and defense


Job description

You will serve as a Construction Engineer (GS-0801, GS-0808) within the Project Management & Engineering Branch, Resident Officer in Charge of Construction (ROICC) New London, of Naval Facilities Engineering Systems Command (NAVFAC) Mid-Atlantic.Qualifications:In addition to the Basic Requirements for this position, your resume must also demonstrate at least one year of specialized experience at or equivalent to the GS-11 grade level or pay band in the Federal service or equivalent experience in the private or public sector performing the following: 1) Overseeing and providing construction engineering support for capital improvement projects including military construction and facilities major renovations; 2) Managing or providing significant assistance to the management of capital improvement projects from conception through close-out, to include scope schedule, and cost; 3) Monitoring construction contractor quality and safety programs via available data and metrics and by conducting site visits; 4) Providing recommendations by resolving project problems due to design errors, unforeseen conditions or changes in criteria; and 5) Preparing and presenting briefs related to scopes of work, design reviews, contract negotiations, etc.
Additional qualification information can be found from the following Office of Personnel Management website:
https://www.opm.gov/policy-data-oversight/classification-qualifications/general-schedule-qualification-standards/#url=List-by-Occupational-Series
https://www.opm.gov/policy-data-oversight/classification-qualifications/general-schedule-qualification-standards/0800/general-engineering-series-0801/
https://www.opm.gov/policy-data-oversight/classification-qualifications/general-schedule-qualification-standards/0800/architecture-series-0808/
Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., professional, philanthropic, religious, spiritual, community, student, social). Volunteer work helps build critical competencies, knowledge, and skills and can provide valuable training and experience that translates directly to paid employment.
Education:Series 0801 General Engineer
Applicants for the Professional Engineering Series must meet the following basic education requirements of the Office of Personnel Management (OPM) Qualifications Standards Manual:

A) Successful completion of a professional engineering degree. To be acceptable, the program must: (1) lead to a bachelor's degree (or higher) in a school of engineering with at least one program accredited by the Accreditation Board for Engineering and Technology (ABET); or (2) include differential and integral calculus and courses (more advanced than first-year physics and chemistry) in five of the following seven areas of engineering science or physics: (a) statics, dynamics; (b) strength of materials (stress-strain relationships); (c) fluid mechanics, hydraulics; (d) thermodynamics; (e) electrical fields and circuits; (f) nature and properties of materials (relating particle and aggregate structure to properties); and (g) any other comparable area of fundamental engineering science or physics, such as optics, heat transfer, soil mechanics, or electronics. Such education must demonstrate the knowledge, skills, and abilities necessary to do the work of the position.
OR
Current registration as an Engineer Intern (EI), Engineer in Training (EIT), or licensure as a Professional Engineer (PE) by any State, the District of Columbia, Guam, or Puerto Rico. Absent other means of qualifying under this standard, those applicants who achieved such registration by means other than written test (e.g., State grandfather or eminence provisions) are eligible only for positions that are within or closely related to the specialty field of their registration For more information about EI and EIT registration requirements, please visit the National Society of Professional Engineers website at: http://www.nspe.org
OR
Evidence of having successfully passed the Fundamentals of Engineering (FE) examination or any other written test required for professional registration by an engineering licensure board in the various States, the District of Columbia, Guam, and Puerto Rico The FE examination is not administered by the U. S. Office of Personnel Management. For more information, please visit: http://www.nspe.org/Licensure/HowtoGetLicensed/index.html.
OR
Successful completion of at least 60 semester hours of courses in the physical, mathematical, and engineering sciences and in engineering that included the courses specified in the basic requirements under paragraph A (above). The courses must be fully acceptable toward meeting the requirements of an engineering program as described in paragraph A (above)
OR
Successful completion of a curriculum leading to a bachelor's degree in an appropriate scientific field, e.g., engineering technology, physics, chemistry, architecture, computer science, mathematics, hydrology, or geology, may be accepted in lieu of a bachelor's degree in engineering, provided the applicant has had at least one year of professional engineering experience acquired under professional engineering supervision and guidance. Ordinarily, there should be either an established plan of intensive training to develop professional engineering competence, or several years of prior professional engineering-type experience, e.g., in interdisciplinary positions.
Series 0808 Architect
Applicants for the Professional Architecture Series must meet the following basic education requirements of the Office of Personnel Management (OPM) Qualifications Standards Manual:

Successful completion of a bachelor's or higher degree in architecture.
OR
Successful completion of a bachelor's or higher degree in a field related to architecture that included 60 semester hours of course work in architecture or related disciplines of which at least (1) 30 semester hours were in architectural design, and (2) 6 semester hours were in each of the following: structural technology, properties of materials and methods of construction, and environmental control systems.
OR
Have a combination of college-level education, training, and/or technical experience that furnished (1) a thorough knowledge of the arts and sciences underlying professional architecture, and (2) a good understanding, both theoretical and practical, of the architectural principles, methods, and techniques and their applications to the design and construction or improvement of buildings. The curriculum for a degree is in either architecture or architectural engineering and covers function, esthetics, site, structure, economics, mechanical-electrical, and other engineering problems related to the design and construction of buildings primarily (but not exclusively) intended to house human activities OR you lack a degree in architecture, but have 1 year of experience in an architect's office or in architectural work for each year short of graduation from a program of study in architecture that demonstrates that you have acquired a thorough knowledge of the fundamental principles and theories of professional architecture. (Note - In the absence of college courses, 5 years of such experience is required).Employment Type: OTHER

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