1

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

Senior Data Engineer

Bloomfield, CT · On-site

$105K - $143K/yr

Senior Data Engineer Location: Bloomfield, CT; Denver, CO; Austin, TX; NYC, NY; virtual work is ... Understanding of Machine learning frame works (e.g. Scikit learning, Scipy) * Understanding and 1+ ...

The role of AI Engineer involves developing and operationalizing machine learning models, ensuring data quality, and collaborating with business and technology teams to create analytics solutions.

Data Engineer

Newington, CT

$114K - $137K/yr

The Data Engineer is a strategic technical role responsible for architecting, building, and ... In addition, this role leads the operationalization of machine learning models, ensuring they are ...

Data Engineer

Newington, CT

$114K - $136K/yr

The Data Engineer is a strategic technical role responsible for architecting, building, and ... In addition, this role leads the operationalization of machine learning models, ensuring they are ...

The role involves ensuring data quality, developing machine learning models, and translating ... Required : • Strong programming skills in Python • Hands-on experience with AI/ML frameworks:

AI Data Engineer - Manager

Hartford, CT · On-site

$115K - $138K/yr

AI Data Engineer - Manager Our Human Capital practice is at the forefront of transforming the ... Lead the development of AI models (e.g., machine learning, natural language processing, computer ...

AI and Data Science Engineer III

Hartford, CT · On-site +1

$115K - $138K/yr

Deliver governed datasets and feature engineering and serving patterns for machine learning training and real-time inference, including online and offline consistency, caching, latency targets, and ...

CTIO AI Engineering Manager

Hartford, CT · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

NGA AI Engineer Manager

Hartford, CT · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

AI Engineer

Hartford, CT · On-site

$115K - $138K/yr

... Machine Learning Overview The Infosys Data and Analytics (DNA) unit is at the forefront of ... Required Skill and Experience Strong programming skills in Python Hands-on experience with AI/ML ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

next page

Showing results 1-20

Machine Learning Engineer information

See Avon, CT salary details

$31K

$126.7K

$190.4K

How much do machine learning engineer jobs pay per year?

As of Jun 15, 2026, the average yearly pay for machine learning engineer in Avon, CT is $126,702.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,900.00 and $152,500.00 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.

What cities near Avon, CT are hiring for Machine Learning Engineer jobs? Cities near Avon, CT with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Avon, CT as of June 2026, with employment types broken down into 97% Full Time, 2% Part Time, and 1% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $126,702 per year, or $60.9 per hour.

Contact Center AI Tech Lead

Purple Drive Technologies

Hartford, CT • On-site

Full-time

Posted 9 days ago


Job description

Overview:
Job Description - Google CCAI / Contact Center AI Tech Lead
As an AI Tech Lead, you will be in charge of designing and implementing AI capabilities for a Contact Center platform in a Healthcare Payer enterprise.
You will work closely with Cloud and Machine Learning engineers, as well as the CRM development team to ensure the proper integration of AI technologies into the platform.
You will be responsible for the strategy, design, implementation, and maintenance of AI solutions.
This role requires a highly skilled professional with a deep understanding of AI technologies and the ability to collaborate effectively with a diverse team.
The ideal candidate will have a strong background in data science and a proven track record in the industry.
Mandatory Experience:
  • Google CCAI (Google Contact Center AI)
  • Strong Contact Center domain experience

Responsibilities:
  • Design and develop AI applications and infrastructure for the Contact Center platform.
  • Collaborate with Cloud and Machine Learning engineers, as well as the development team, to ensure seamless integration of AI technologies.
  • Stay current with the latest AI trends and technologies, especially Google GCP or Azure AI for Contact Center.
  • Create and maintain AI models and algorithms.
  • Conduct AI research to improve existing systems and develop new technologies.
  • Identify opportunities for AI solutions within the organization and propose strategic plans.
  • Train team members and stakeholders on AI and its applications.
  • Ensure compliance with data privacy regulations in AI applications.
  • Monitor the performance of AI systems and make necessary adjustments.