ZipRecruiter

Log In

1

Machine Learning Engineer Jobs in New London, CT

Kanak Elite Services Inc

AI Developer

Conantville, CT · On-site

AI Developer Location : Greenwich, CT Hybrid (Need local candidate) Duration : 6+ Months Interview ... Develop and maintain AI and machine learning models using AWS Bedrock, SageMaker, and Python-based ...

Whelen Engineering

Manufacturing Engineer I

Chester, CT · On-site

$73K - $95K/yr

Still learning the fundamentals of the Manufacturing Engineering Production Support role ... Basic machine shop experience and knowledge of measurement techniques Physical demands and ...

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 ...

next page

Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in New London, CT

Machine Learning Engineer information

See New London, CT salary details

$31.3K

$128K

$192.3K

How much do machine learning engineer jobs pay per year?

As of Jul 24, 2026, the average yearly pay for machine learning engineer in New London, CT is $127,964.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,900.00 and $154,000.00 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.

More about Machine Learning Engineer jobs
What are popular job titles related to Machine Learning Engineer jobs in New London, CT? For Machine Learning Engineer jobs in New London, CT, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in New London, CT look for? The top searched job categories for Machine Learning Engineer jobs in New London, CT are:
What cities near New London, CT are hiring for Machine Learning Engineer jobs? Cities near New London, CT with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in New London, CT as of July 2026, with employment types broken down into 82% Full Time, 11% Part Time, 2% Contract, and 5% Nights. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $127,964 per year, or $61.5 per hour.
AI Engineer - Software

AI Engineer - Software

General Dynamics Electric Boat

Groton, CT

Full-time

Posted 12 hours 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

68th of 535 rated manufacturers

Job description

The IT Advanced Technology Group at Electric Boat is seeking a highly skilled and innovative AI Engineer to join our team and support the design, development, and deployment of advanced machine learning (ML) and artificial intelligence (AI) solutions. This role involves hands-on work with data wrangling, model development, automated agents, and exploratory research into emerging AI technologies and methodologies. The ideal candidate is both technically strong and forwardthinking, with a passion for applying AI to solve complex business problems.

Responsibilities Include:

Machine Learning & Model Development

  • Design, train, validate, and deploy machine learning models using modern frameworks and best practices.
  • Build endtoend ML pipelines that include data ingestion, preprocessing, feature engineering, training, evaluation, and monitoring.
  • Optimize models for performance, scalability, and efficiency.

Data Wrangling & Analysis

  • Collect, clean, transform, and structure complex datasets from diverse sources.
  • Perform exploratory data analysis to identify trends, anomalies, and opportunities.
  • Develop automation for data processing workflows and ensure high data quality.

AI Agents & Automation

  • Create intelligent agents capable of autonomous decisionmaking, workflow automation, and contextual reasoning.
  • Integrate agents with internal systems, APIs, and knowledge bases.
  • Evaluate agent performance and iterate based on measurable outcomes.

Research & Emerging Technology Exploration

  • Stay current with the rapidly evolving AI/ML landscape, including new algorithms, architectures, tools, and best practices.
  • Prototype innovative AI solutions using cuttingedge techniques such as LLMs, RAG pipelines, multi-agent systems, and generative models.
  • Develop technical briefs, proofs of concept, and recommendations for adopting new technologies.

Collaboration & Communication

  • Work closely with software engineers, data scientists, product teams, and stakeholders to translate business needs into AI solutions.
  • Document technical designs, research findings, and model performance.
  • Provide guidance and mentorship on AI/ML concepts and toolsets.

Required:

  • Bachelor's of Science degree or Master’s degree in Computer Science, Data Science, or AI Engineering
  • 5+ years of  post-graduate related experience in developing software applications

Preferred:

  • Strong proficiency in Python and familiarity with ML libraries such as TensorFlow, PyTorch, scikit-learn, or similar.
  • Strong proficiency with application APIs, web services, and data management approaches in applications
  • Experience with data wrangling tools and technologies (Pandas, SQL, ETL systems).
  • Solid understanding of machine learning algorithms, statistical modeling, and model evaluation.
  • Experience working with LLMs or generative AI models.
  • Knowledge of cloud platforms (Azure, AWS, GCP) and containerization technologies.
  • Experience building AI agents or autonomous systems.
  • Familiarity with vector databases, RAG architectures, or multimodal models.
  • Exposure to MLOps practices (CI/CD, model monitoring, feature stores).
  • Contributions to AI research, open-source tools, or AIrelated publications.
  • Knowledge of distributed computing or GPU optimization.

  • Excellent verbal and written communication skills
  • Strong organizational and interpersonal skills
  • Ability to multi-task in a fast-paced environment
  • Ability to work on a cross-functional team as well as independently
  • Curiosity, adaptability, and enthusiasm for continuous learning.

Inside

What General Dynamics Electric Boat employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply