ZipRecruiter

Log In

1

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

ExlService Holdings, Inc.

GCP Cloud Engineer

Hartford, CT

$115K - $138K/yr

AI & Machine Learning * Experience supporting ML/AI workflows and pipelines * Healthcare Domain ... Data Engineering & Pipeline Development * Design, develop, and maintain scalable ETL/ELT pipelines ...

ExlService Holdings, Inc.

GCP Cloud Engineer

Hartford, CT · On-site

$115K - $138K/yr

Develop feature pipelines and data transformations for machine learning use cases. * Support use cases such as: * Patient risk scoring * Quality and safety analytics * Cloud & GCP Engineering * Build ...

Bausch + Lomb

AI Agent ML Engineer

Hartford, CT

$165K - $190K/yr

The AI Agent & ML Engineer will design, build, and optimize intelligent agents powered by advanced machine learning models, enabling process automation and decision support across Bausch + Lombs ...

CVS Health

Senior Data Engineer (Requiring GCP)

Hartford, CT · On-site

$106K - $145K/yr

They are seeking a Senior Data Engineer to join their Medicare Member Experience data science team ... workflows for machine learning models. Responsibilities : • Build and maintain the cloud ...

Pwc

US Tech - 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 ...

PCX Aerosystems

Data Engineer

Newington, CT · On-site

$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 Whiteside Agency

Senior Data Engineer

Hartford, CT · On-site

$139K - $230K/yr

... Machine Learning, and AI initiatives across Travelers. As a Senior Engineer, you serve as a ... technical anchor within your engineering circle: mentoring peers, driving SDLC+ and engineering ...

Deloitte

Google AI Lead Architect

Hartford, CT · On-site

$55.75 - $76.50/hr

Preferred : • Google Professional Machine Learning Engineer certification or the equivalent ML certification. • Master's degree in technology-related discipline. • 2+ years' leading high ...

Tiger Analytics Inc.

GenAI Data Engineer

Hartford, CT · Remote

$117K - $140K/yr

Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted ... As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines ...

Tiger Analytics Inc.

GenAI Data Engineer

Hartford, CT

$115K - $138K/yr

Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted ... As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines ...

Tiger Analytics Inc.

GenAI Data Engineer

Hartford, CT · On-site +1

$115K - $138K/yr

Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted ... As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines ...

Pwc

AI & GenAI Data Scientist - Manager

Hartford, CT · On-site

$99K - $232K/yr

In this role at PwC, you will apply data, algorithms, and software engineering to build and deploy software and platform systems that create Artificial Intelligence and Machine Learning-based ...

next page

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 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.

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 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.
GCP Cloud Engineer

GCP Cloud Engineer

ExlService Holdings, Inc.

Hartford, CT

$115K - $138K/yr

Full-time

Posted 11 days ago

ExlService Holdings rating

8.3

Company rating: 8.3 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

60th of 428 rated business services

Job description

We are seeking a highly skilled Data Engineer with strong expertise in Python, Google Cloud Platform (GCP), and AI-enabled data solutions. The ideal candidate will build scalable data pipelines and support advanced analytics initiatives within the healthcare domain, with a focus on Medicare Part D data and patient safety outcomes. The ideal profile should reflect a higher level of technical proficiency, problem-solving ability, and domain understanding particularly in building robust data solutions, working with complex healthcare datasets, and collaborating effectively across data science, clinical, and business teams.

  • Technical Skills
  • Strong programming Handson experience in Python/ Pyspark(mandatory)
  • Expertise in:
    • SQL (advanced querying, performance tuning)
    • Data modeling (star/snowflake schemas)
  • Hands-on experience with GCP data services(Big Query, Dataproc)
  • Experience with distributed processing frameworks (e.g., Apache Spark)
  • Familiaritywith CI/CD pipelinesand DevOps practices
  • AI & Machine Learning
  • Experience supporting ML/AI workflows and pipelines
  • Healthcare Domain Knowledge (Preferred but Strongly Desired)
  • Experience working with healthcare datasets(claims, EHR, clinical data)
  • Familiarity with Medicare/Medicaid data structures and reporting
  • Understanding of value-based care and quality measures
  • Patient Safety Knowledge (Preferred)
  • Knowledge of patient safety frameworks and indicators
  • Experience supporting:
    • Quality reporting programs (e.g., CMS measures)
    • Clinical risk and compliance analytics
  • Data Engineering & Pipeline Development
  • Design, develop, and maintain scalable ETL/ELT pipelinesfor structured and unstructured healthcare data.
  • Build robust data ingestion frameworks from multiple sources (Medical claims, RX Claims, Membership etc.).
  • Ensure data quality, integrity, and governanceacross all pipelines.
  • Optimize data workflows for performance, reliability, and cost efficiency on GCP.
  • AI & Advanced Analytics Enablement
  • Collaborate with data scientists to operationalize AI/ML modelsin production environments.
  • Develop feature pipelines and data transformations for machine learning use cases.
  • Support use cases such as:
    • Patient risk scoring
    • Quality and safety analytics
  • Cloud & GCP Engineering
  • Build and manage data infrastructure using GCP services such as:
    • BigQuery
    • Cloud Composer Workflow
    • Cloud Storage
    • Dataproc / Spark
  • Implement data lake and data warehouse architectureson GCP.
  • Ensure compliance with HIPAA and healthcare data security standards.
  • Healthcare & Medicare Data Management
  • Work with Medicare datasetsincluding:
    • Claims data (Part D)
    • Provider and beneficiary data
  • Enable analytics for quality measures, patient outcomes, and regulatory reporting.
  • Patient Safety & Compliance
  • Develop solutions to monitor and improve patient safety indicators (PSIs)and care quality.
  • Build data models supporting:
    • Adverse event detection
    • Medication safety
    • Clinical quality measures
  • Ensure compliance with healthcare regulations and data privacy standards.

Apply