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

NAVA Software Solutions

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+ ...

Infosys

AI Engineer

Hartford, CT · On-site

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.

Applied Aerospace & Defense

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 ...

Applied Aerospace & Defense

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 ...

Pwc

CTIO AI Engineering Manager

Hartford, CT

$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 ...

The Hartford

Staff Software Engineer - AI

Hartford, CT · On-site

$127K - $191K/yr

Senior Staff Software Engineer - IE07HE We're determined to make a difference and are proud to be ... Design and develop machine learning techniques that allow agents to learn from experience and adapt ...

Pwc

NGA AI Engineer Manager

Hartford, CT

$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 ...

Infosys

AI Engineer

Hartford, CT · On-site

... AI Engineer to join their Data and Analytics unit. The role involves participating in data ... machine learning techniques and collaborate with technology teams to operationalize them into ...

Infosys Limited Digital

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 ...

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Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Avon, CT

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 Jul 22, 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.

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 cities near Avon, CT are hiring for Machine Learning Engineer jobs? Cities near Avon, CT with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Avon, CT as of July 2026, with employment types broken down into 91% Full Time, 5% Part Time, and 4% 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.
Data Engineer

Data Engineer

The Hartford Financial Services Group, Inc.

Hartford, CT • On-site

$115K - $138K/yr

Full-time

Posted 8 days ago

Job description

Data Engineer - GE08AE
We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.
Data Engineer (AI & Data Platforms)
The Hartford seeks a driven, team-focused Data Engineer to build and support data pipelines, cloud-based data platforms, and Machine Learning Operations (MLOps) services for the Customer Operations Data Science team.
The Hartford is developing industry-leading AI and machine learning capabilities to improve customer experience (CX) at scale. Within Customer Operations Data Science, we build modern AI products that optimize customer interactions across omnichannel journeys, supporting operational areas such as the Contact Center, Digital, Premium Audit, and Billing.
As a Data Engineer, you will contribute to the development of scalable data platforms and production-ready data pipelines that enable analytics, machine learning, and AI solutions. Working closely with data scientists, machine learning engineers, product owners, and business partners, you will help deliver reliable data assets and services that create measurable business value.
Our Core Values
  • We build AI solutions, not models. We are thoughtful in supporting the end-to-end business problem, with an eye toward scalable and maintainable systems.
  • We are trusted and transparent. We collaborate closely with our business and technology partners and are mindful of their capacity to absorb change.
  • We provide assets that are safe to buy. Our products include monitoring, observability, and governance to ensure long-term success.
  • We will earn the right to influence. With humble confidence, we listen carefully and become trusted partners in problem solving.
  • We are practical and evolutionary. We first deliver a minimally viable solution and expand its sophistication over time based on customer feedback and business value.

Responsibilities
  • Design, build, and maintain scalable ETL/ELT data pipelines and integrations.
  • Develop and support data ingestion, transformation, and delivery solutions using cloud-native technologies.
  • Implement data quality controls, monitoring, and observability capabilities to ensure reliable data products.
  • Support machine learning and AI solutions through data engineering, feature engineering, and operationalization activities.
  • Build reusable frameworks, components, and automation capabilities to increase delivery efficiency.
  • Collaborate with Data Science, Enterprise Data, Cloud Enablement, Architecture, and Business teams to deliver data solutions.
  • Develop and maintain CI/CD pipelines and Infrastructure as Code (IaC) assets to support cloud-based deployments.
  • Assist with the deployment, monitoring, and support of production data and AI services in AWS and GCP environments.
  • Troubleshoot and resolve data pipeline, integration, and platform performance issues.
  • Participate in Agile ceremonies, code reviews, technical documentation, and continuous improvement activities.
  • Follow and promote software engineering, DataOps, and MLOps best practices.

Minimum Requirements
  • Must be authorized to work in the U.S. now and in the future.
  • Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field, or equivalent work experience.
  • Experience building and supporting data pipelines in cloud-based environments.
  • Experience with SQL development and relational database concepts.
  • Experience with Python or similar programming languages.
  • Familiarity with AWS and/or GCP cloud services.
  • Experience with source control systems such as GitHub.
  • Experience with CI/CD tools such as GitHub Actions, Jenkins, or similar platforms.
  • Experience with Infrastructure as Code (Terraform, CloudFormation, or similar technologies).
  • Familiarity with workflow orchestration tools such as Apache Airflow, Cloud Composer, or similar platforms.
  • Experience working with data warehouse technologies such as Snowflake, Redshift, BigQuery, or similar platforms.
  • Understanding of data quality, data governance, and data lifecycle management principles.
  • Familiarity with API integration and cloud-native application development concepts.
  • Basic understanding of machine learning workflows and model deployment concepts.

Preferred Skills
  • Strong understanding of data structures and software development fundamentals.
  • Experience building and optimizing large-scale data pipelines.
  • Experience with Docker, Kubernetes, and containerized application deployment.
  • Experience supporting MLOps or AI platform capabilities.
  • Experience with data observability and monitoring tools.
  • Familiarity with dbt, Spark, Hadoop, or other modern data engineering technologies.
  • Experience working in Agile development environments.
  • Exposure to Generative AI technologies, Agentic AI workflows, vector databases, or LLM-powered applications.
  • Experience working in highly regulated industries such as insurance or financial services.

Qualifications
  • 2+ years of experience in data engineering, software engineering, analytics engineering, or related technical roles.
  • 2+ years of Python development experience.
  • 2+ years of SQL development experience.
  • Experience developing, maintaining, or supporting ETL/ELT data pipelines.
  • Experience working with cloud technologies such as AWS, GCP, or Azure.
  • Experience using CI/CD pipelines and Infrastructure as Code practices.
  • Experience working with modern data platforms such as Snowflake, BigQuery, or Redshift.
  • Exposure to data quality, monitoring, and operational support processes.
  • Familiarity with emerging data-centric technologies including Generative AI, Agentic workflows, and embedding LLMs into automated processes.

This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday). Candidates must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.
Compensation
The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford's total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:
$100,960 - $151,440
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
About Us | Our Culture | What It's Like to Work Here | Perks & Benefits
Hartford logo

About Hartford

Sourced by ZipRecruiter

Hartford Financial Services Group, widely recognized as The Hartford, is a renowned company based in Hartford, CT, US. Established in 1810, it has evolved into an industry leader in the insurance and financial services sector, proudly serving more than one million businesses in the US. The Hartford is committed to offering a gamut of insurance products that include homeowners, automobile, and business insurance as well as employee benefits and mutual funds. The company’s core values revolve around customer-focused innovations, diversity and inclusion, and ethical dealings that have earned them a customer-centric reputation. This shapes their mission which revolves around aiding their clients to overcome unforeseen obstacles and enhancing their wealth over time. Among the company's noted accomplishments is being consistently listed among the World's Most Ethical Companies, a testament to their unwavering commitment towards responsible business practices.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

Hartford, CT, US

Year founded

1810

Social media

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