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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 ...

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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 Platform Director- Data Engineering

AI Platform Director- Data Engineering

First Citizens Bank

Carolina, RI

$254K/yr

Full-time

Posted 2 days ago

First Citizens Bank rating

7.6

Company rating: 7.6 out of 10

Based on 105 frontline employees who took The Breakroom Quiz

85th of 150 rated banks

Job description

Overview

We are seeking an experienced Director to lead the AI platform engineering and enablement functions within our expanding Cloud Data and AI Platform organization. This role is instrumental in building, operationalizing, and governing the next-generation AI and machine learning ecosystem that powers advanced analytics and responsible AI adoption across the bank. You will own the end-to-end AI lifecycle—from data and model development to MLOps, deployment, governance, and responsible AI compliance in a regulated financial environment.

As a seasoned technology leader, you will bring your expertise in enterprise AI architecture, model operations, and platform engineering to partner with key business, technology, and governance stakeholders—ensuring AI initiatives are responsibly implemented, well-controlled, and deliver measurable value. 


Responsibilities

AWS AI/ML Platform Ownership

  • Architect and lead AI/ML workloads on AWS including:
    • Amazon SageMaker (training, deployment, model registry)
    • AWS Bedrock (foundation models and GenAI use cases)
    • AWS Lambda, ECS, EKS for model serving
    • S3, Glue, Snowflake for data pipelines
  • Define enterprise standards for MLOps, feature stores, and model lifecycle management
  • Build and maintain integrations with enterprise platforms for data ingestion, metadata management, tokenization, and control evidence generation. 
  • Continuously enhance the platform’s automation, resilience, and observability, ensuring robust end-to-end telemetry for both model and data pipelines. 
  • Collaborate with Enterprise Risk, Legal, Compliance, and Model Risk partners to embed Responsible AI principles and audit-ready control evidence directly into platform design. 

Machine Learning & GenAI Execution

  • Oversee development of ML models across all business units including Fraud detection systems, Credit scoring and risk modeling, Customer segmentation and personalization, Liquidity related modeling etc.
  • Lead GenAI initiatives using LLMs for Document intelligence, AI copilots etc.

 

Data & Engineering Collaboration

  • Partner with data engineering teams to ensure high-quality, governed datasets
  • Define feature engineering and data product standards in Snowflake / data lake environments
  • Integrate real-time streaming data for low-latency decision systems

 

Model Governance & Risk Compliance

  • Define and enforce standards, patterns, and guardrails for model deployment, explainability, lineage, and monitoring in alignment with enterprise risk, compliance, and security frameworks. 
  • Partner closely with leaders across Responsible AI Governance, AI Portfolio Management, AI Fluency & Engagement, and Applied Data Science & GenAI, in collaboration with enterprise risk partners, to implement a responsible AI framework that embeds audit-ready control evidence and governance mechanisms directly into the platform’s core design to ensure the platform supports scalable, ethical, compliant, and high-impact AI delivery. 
  • Implement model explainability (SHAP, LIME, interpretability frameworks)
  • Establish responsible AI policies (bias detection, fairness, auditability)

 

Team Building & Leadership

  • Develop and mentor engineering talent, championing Agile practices, continuous learning, and adoption of emerging AI and data engineering technologies. 
  • Mentor senior technical leaders and establish engineering best practices
  • Oversee technical due diligence, onboarding, and management of strategic AI and GenAI vendors and tools, ensuring compatibility with enterprise architecture and control

Qualifications

Bachelor's Degree and 8 years of experience in Information Technology including application development, support roles, and management. OR High School Diploma or GED and 12 years of experience in Information Technology including application development, support roles, and management.

Qualifications

  • Deep hands-on experience building production ML systems on AWS
  • 2+ years in AI/ML, data science, or data engineering leadership roles
  • Strong knowledge of:
    • Machine learning (XGBoost, deep learning, NLP, time series)
    • MLOps practices (CI/CD, model monitoring, drift detection)
    • Distributed systems and cloud architecture
  • Strong programming background in Python + SQL (Scala/Java a plus)
  • Experience working in regulated environments with model governance

Preferred Qualifications

  • Experience with Generative AI / LLM platforms (Bedrock, OpenAI, Claude APIs)
  • Experience in financial services, banking, fintech, or insurance
  • Familiarity with data platforms like Snowflake, Databricks

#LI-JM1

Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.

Qualifications:

Bachelor's Degree and 8 years of experience in Information Technology including application development, support roles, and management. OR High School Diploma or GED and 12 years of experience in Information Technology including application development, support roles, and management.

Qualifications

  • Deep hands-on experience building production ML systems on AWS
  • 2+ years in AI/ML, data science, or data engineering leadership roles
  • Strong knowledge of:
    • Machine learning (XGBoost, deep learning, NLP, time series)
    • MLOps practices (CI/CD, model monitoring, drift detection)
    • Distributed systems and cloud architecture
  • Strong programming background in Python + SQL (Scala/Java a plus)
  • Experience working in regulated environments with model governance

Preferred Qualifications

  • Experience with Generative AI / LLM platforms (Bedrock, OpenAI, Claude APIs)
  • Experience in financial services, banking, fintech, or insurance
  • Familiarity with data platforms like Snowflake, Databricks

#LI-JM1

Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.

Education:UNAVAILABLEEmployment Type: FULL_TIME

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