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

ResultStack

Sr. Data Scientist

Carolina, RI · On-site

You'll work across operations, engineering, and leadership to build predictive systems that ... They will be well versed in AI & Machine Learning. Having Hands-On experience with LLM's, NLP ...

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 ...

Pfizer

Senior Scientist, Automation

Groton, CT · On-site

$93.60K - $156K/yr

Develop and implement synergistic digital tools for machine learning and self-optimization to ... Partner with process chemists and engineers on suitable experimentation to deliver CRD workflows ...

Pfizer, Inc.

Senior Scientist, Automation

Groton, CT · On-site

$93.60K - $156K/yr

Develop and implement synergistic digital tools for machine learning and self-optimization to ... Partner with process chemists and engineers on suitable experimentation to deliver CRD workflows ...

Henpen Corporation

Power Electronics Engineer

Groton, CT

$111.40K - $131.80K/yr

... opportunities and learning experiences. You will work in a small company environment where ... machines and/or drives Experience working with acoustic transducers Familiarity with power ...

Henpen Corporation

Power Electronics Engineer

Groton, CT

$111.40K - $131.80K/yr

... opportunities and learning experiences. You will work in a small company environment where ... experience designing electric machines and/or drives • Experience working with acoustic ...

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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 May 30, 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 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 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 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 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 jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.

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 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
Sr. Data Scientist

Sr. Data Scientist

ResultStack

Carolina, RI • On-site

Full-time

Posted 6 days ago

Job description

Must be a US Citizen or Hold a Green Card


ABOUT THE ROLE

We are looking to hire a Data Scientist who can transform the

complexity of global shipping and logistics into clear, actionable

intelligence. You'll work across operations, engineering, and leadership

to build predictive systems that optimize routes, forecast demand, and

surface insights that keep cargo moving. This is a high-impact role at the

intersection of data science, operational expertise, and emerging AI.

CORE REQUIREMENTS

This candidate will have Dashboard & BI Tooling. Being Fluent in

Tableau, Power BI, Looker, or equivalent. They will be able to model data

and present it for both technical and executive audiences.

They will have Complex Data Fluency. Being very comfortable

wrangling large, noisy datasets --- EDI records, tracking logs, port data,

weather overlays, and multi-model feeds.

They will do Predictive Modeling. Having proven experience building

ML models from messy. High-dimensional datasets (time series, sensor

data, ETA prediction, etc.).

They will be well versed in AI & Machine Learning. Having Hands-On

experience with LLM's, NLP, computer vision, or operations research

applied to real-world logistics problems.

This candidate must also be excellent in Collaboration &

Communication. They can translate model outputs into business

decisions. They will also possess strong documentation habits and

cross-functional alignment skills.

WHAT YOU'LL WORK ON

Route optimization and transit time prediction models Anomaly

detection in shipment and carrier data Real-time operational

dashboards for fleet and port performance AI-assisted demand

forecasting for freight capacity planning Cross-team data

infrastructure and model deployment support.

REQUIREMENTS

6+ Years in shipping, freight, logistics, or supply chain,

Understand how cargo and data both move.

NICE TO HAVES

Python, R, or SQL --- scripting and querying at production scale.

Software Development Principles: version control (Git), CI/CD, API

integration. Familiarity with containerization (Docker) or cloud

platform (AWS, GCP, Azure). Experience building data pipelines or ETL

workflows.