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Machine Learning Engineer Jobs in New London, CT

Henpen Corporation

Power Electronics Engineer

Groton, CT · On-site

$111K - $131K/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

$111K - $131K/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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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 Jun 29, 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.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

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-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies 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 they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

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 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 June 2026, with employment types broken down into 1% As Needed, 97% Full Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $127,964 per year, or $61.5 per hour.
Forward Deployed Full-Stack Engineer (Groton, CT / Senior)

Forward Deployed Full-Stack Engineer (Groton, CT / Senior)

Spear AI

Groton, CT • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 23 days ago

Key responsibilities

  • Build out application components and pages.

  • Implement historical and real-time data feeds using WebGPU.

  • Design and develop data models using Postgres and Apache Iceberg.

Job description

We're seeking a skilled Forward Deployed Full-Stack Engineer to build the next-generation data management and artificial intelligence platform for maritime domain awareness.
As a forward-deployed engineer, you'll work on-site with customers - writing code, integrating systems, and solving hard problems in the field. You're part engineer, part technical advisor, and wholly accountable for making the mission succeed. The position requires an active U.S. Secret clearance.
Spear AI is a growing defense contracting company dedicated to delivering cutting-edge solutions that support our nation's security. As we expand, we're building a culture where innovation meets mission-critical work. We operate with a flat organizational structure that empowers every team member to make an impact, collaborate directly with leadership, and contribute to projects that matter. Whether you're joining our Hardware, Software, or Services division, you'll work alongside talented professionals who are committed to excellence and advancing the capabilities that keep our nation safe and secure.
Spear AI builds sonobuoy sensors that are deployed into the water and collect edge data. We also work with the U.S. Navy to collect and process their SONAR data. You'll have an opportunity to work on real-world projects that directly impact warfighter capabilities and mission success.
What you'll do
We're a small team wearing many hats, and you'd have a wide variety of responsibilities that include:
  • Build out application components and pages.
  • Implement historical and real-time data feeds using WebGPU.
  • Design and develop data models using Postgres and Apache Iceberg.
  • Modify real-time data pipelines using MQTT and Redpanda.
  • Modify offline data pipelines using Dagster for batch processing.
  • Modify and integrate machine learning models or other algorithms into the application.
  • Improve local development and CI/CD using modern tooling and GitHub Actions.

Who you are
We're looking for someone with strong Full-Stack Engineering skills who shares our most important values:
  • You're fanatical about polish. Every detail matters. You love to make sure your code is linted, formatted, fully typed, and has 100% test coverage.
  • You care about correctness. You take pride in the fact that downstream consumers trust libraries and services you build.
  • You obsess over performance. You daydream about Lighthouse scores and query speed.
  • You dive deep. It's important for you to really know how things work. You're always building prototypes and setting up experiments to reinforce your understanding.
  • You live on the bleeding edge. You've got a long list of upcoming platform features you're excited about and can't wait for the next nightly to drop.
  • You're a great teacher. You know how to break down a concept for a specific audience and make it click with them in a way that gets them excited.

Why work with us
  • We ship - We don't work on 18-month projects that are irrelevant before they're even finished.
  • Our work has impact - We build products that are deployed to U.S. submarines and integrate with the sonobuoys we manufacture.
  • We're growing responsibly - We have the resources to hire a lot more people, but we don't want to build a massive team of people who don't share our values.
  • We're profitable - We aren't burning through cash trying to make the business work. But we also have investors who believe in us and are committed to our success.
  • We care about doing great work - You don't need permission to sweat the details here.
  • We don't take ourselves too seriously - We're building products that make the world safer. But we don't let that get to our heads.
Important skills
  • Active Secret Clearance.
  • Expertise in TypeScript.
  • Expertise in CSS, such as TailwindCSS.
  • Experience with React and frontend frameworks such as Next.js.
  • Familiar with state management such as React Context.
  • Experience with Node.js, GraphQL, and REST APIs.
  • Proficiency with SQL/PostgreSQL.
  • Knowledge of Docker and Kubernetes.
  • Knowledge of Python.

Nice to have
  • Experience with IoT devices and sensors.
  • Digital signal processing experience.
  • Geospatial analysis and GIS experience.
  • Familiar with working in monorepos.

What we offer
  • Unlimited PTO - Take the time you need to recharge and maintain work-life balance.
  • Dedicated sick time - Your health and well-being come first.
  • Comprehensive health and benefits - Medical, dental, and vision coverage to keep you and your family protected.
  • 11 Paid Holidays - Enjoy time off throughout the year to celebrate and spend time with loved ones.
  • Professional development - Educational opportunities and resources to help you grow your skills and advance your career.
  • Collaborative environment - Work directly with leadership in our flat organizational structure, where your ideas and contributions matter.
  • Mission-driven work - Contribute to projects that directly support national security and make a real-world impact.
  • Growth opportunities - Join us during an exciting expansion phase where you can help shape our future.

Additional benefit opportunities when you choose Spear AI:
  • 401(k) with company match.
  • Relocation assistance (position dependent).
  • Referral bonuses.
  • Performance bonuses.
  • Life insurance and disability coverage.
  • Technology home office setup stipend.
  • Professional certification reimbursement (position dependent).

We offer competitive compensation tailored to your experience, location, and the impact you'll make. We're committed to equitable pay and will share a range aligned to your level and geography during the hiring process. In accordance with state law, candidates in jurisdictions such as CA, CO, WA, NY, and others, where applicable, will be provided a good-faith salary range upon request and throughout the hiring process. This is a full-time, exempt position under the Fair Labor Standards Act (FLSA) and is not eligible for overtime pay.
Compensation for this position is provided on a salaried basis and is not subject to reduction based on hours worked. At Spear AI, you'll find more than just a job; you'll join a mission-driven team where your work directly contributes to national security. Our flat organizational structure means your voice matters, your ideas reach leadership, and your impact is visible. As we grow, we're committed to building robust processes and infrastructure that support both our mission and our people. We value collaboration, continuous improvement, and the expertise each team member brings to the table. If you're looking for a place to grow professionally while working on projects that truly matter, we'd love to hear from you.
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About Spear AI

Sourced by ZipRecruiter

Industry

Guided missile and space vehicle manufacturing

Company size

11 - 50 Employees

Headquarters location

Washington, DC, US

Year founded

2020

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