ML Engineer Visa Sponsorship Jobs in Connecticut
Connecticut's ml engineer job market is anchored by financial services firms in Stamford, insurance and analytics companies in Hartford, and major research employers like United Technologies and Yale University. Aetna, Cigna, and several hedge fund technology teams actively recruit ml engineers and have established visa sponsorship infrastructure for international candidates.
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Get Access To All JobsINTRODUCTION
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.
The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team.
The Hartford is developing industry‑leading AI and machine learning capabilities to improve the various facets of the Global Specialty underwriting experience. On the Global Specialty Applied AI team, we utilize the latest AI products and frameworks to accelerate the processes that our partners touch day to day and advance the speed and intelligence with which we make our decisions. As a Senior Machine Learning AI Engineer, you will play a critical role in designing, building, and operationalizing production‑grade AI solutions—partnering closely with product, engineering, and platform leaders to deliver measurable impact.
Our core values
We build AI solutions, not models. We are thoughtful in supporting the end-to-end business problem, with an eye to systems design.
We are trusted and transparent. We collaborate tightly with our partners and are mindful of their capacity to absorb change.
We provide assets that are safe to buy. Our products are delivered with a full monitoring solution to ensure our products continue to deliver as expected.
We will earn the right to influence. With humble confidence, we listen carefully to learn from our customers and become partners in problem solving.
* We are practical and evolutional. We first deliver a minimally viable product and over time expand its sophistication based on feedback.
Responsibilities
Research, experiment with, and implement suitable Generative and ML algorithms, tools and technologies.
Participate in identifying and assessing opportunities i.e. value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage.
Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations.
Accountable for deployment design, development and maintenance of both traditional ML and AI models.
Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable presenting new concepts to technical audiences.
Collaborate with partners Enterprise Data, Applied AI, Business, Cloud Enablement Team, and Enterprise Architecture teams.
Delivery of critical milestones for model deployment in the AWS and GCP clouds.
Adopt and promote MLOps best practices to the Data Science community.
MINIMUM REQUIREMENTS
Must be authorized to work in the U.S. now and in the future.
Master’s degree in related field or 5+ years of equivalent experience in a research or DevOps function.
Development experience developing solutions within AWS, GCP or both.
Experience developing repeatable architectural patterns; ability to identify redundancies and eliminate them with these patterns.
Experience building and deploying API services within the Cloud.
Experience building CICD pipeline using Jenkins or equivalent.
Experience with IAC (Infrastructure as Code) including Cloud Formation, Terraform, or equivalents.
Experience in Unix, git, and strong object oriented development experience using Python.
Experience in end to end model development lifecycle, from ideation through post production monitoring.
Experience with workflow automation platforms (Apache Airflow, Autosys, similar).
Basic understanding of Data Science model development life cycle.
Familiarity with emerging data centric technologies such generative AI, Agentic workflows, and embedding LLM’s into automated processes.
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:
$117,200 - $175,800
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
INTRODUCTION
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.
The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team.
The Hartford is developing industry‑leading AI and machine learning capabilities to improve the various facets of the Global Specialty underwriting experience. On the Global Specialty Applied AI team, we utilize the latest AI products and frameworks to accelerate the processes that our partners touch day to day and advance the speed and intelligence with which we make our decisions. As a Senior Machine Learning AI Engineer, you will play a critical role in designing, building, and operationalizing production‑grade AI solutions—partnering closely with product, engineering, and platform leaders to deliver measurable impact.
Our core values
We build AI solutions, not models. We are thoughtful in supporting the end-to-end business problem, with an eye to systems design.
We are trusted and transparent. We collaborate tightly with our partners and are mindful of their capacity to absorb change.
We provide assets that are safe to buy. Our products are delivered with a full monitoring solution to ensure our products continue to deliver as expected.
We will earn the right to influence. With humble confidence, we listen carefully to learn from our customers and become partners in problem solving.
* We are practical and evolutional. We first deliver a minimally viable product and over time expand its sophistication based on feedback.
Responsibilities
Research, experiment with, and implement suitable Generative and ML algorithms, tools and technologies.
Participate in identifying and assessing opportunities i.e. value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage.
Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations.
Accountable for deployment design, development and maintenance of both traditional ML and AI models.
Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable presenting new concepts to technical audiences.
Collaborate with partners Enterprise Data, Applied AI, Business, Cloud Enablement Team, and Enterprise Architecture teams.
Delivery of critical milestones for model deployment in the AWS and GCP clouds.
Adopt and promote MLOps best practices to the Data Science community.
MINIMUM REQUIREMENTS
Must be authorized to work in the U.S. now and in the future.
Master’s degree in related field or 5+ years of equivalent experience in a research or DevOps function.
Development experience developing solutions within AWS, GCP or both.
Experience developing repeatable architectural patterns; ability to identify redundancies and eliminate them with these patterns.
Experience building and deploying API services within the Cloud.
Experience building CICD pipeline using Jenkins or equivalent.
Experience with IAC (Infrastructure as Code) including Cloud Formation, Terraform, or equivalents.
Experience in Unix, git, and strong object oriented development experience using Python.
Experience in end to end model development lifecycle, from ideation through post production monitoring.
Experience with workflow automation platforms (Apache Airflow, Autosys, similar).
Basic understanding of Data Science model development life cycle.
Familiarity with emerging data centric technologies such generative AI, Agentic workflows, and embedding LLM’s into automated processes.
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:
$117,200 - $175,800
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
ML Engineer Job Roles in Connecticut
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Search ML Engineer Jobs in ConnecticutML Engineer Jobs in Connecticut: Frequently Asked Questions
Which companies sponsor visas for ml engineers in Connecticut?
Financial services and insurance companies are among the most active visa sponsors for ml engineers in Connecticut. Cigna, Aetna, and Hartford Financial Services have sponsored H-1B visa workers in machine learning and data science roles. Stamford-based hedge funds and asset managers, including Two Sigma and various quantitative trading firms, also file petitions for ml engineers regularly. Large defense and aerospace contractors with Connecticut operations, such as Raytheon and Pratt & Whitney, round out the sponsoring employer base.
Which visa types are most common for ml engineer roles in Connecticut?
The H-1B visa is the most common sponsorship pathway for ml engineers in Connecticut, given that machine learning engineering typically qualifies as a specialty occupation requiring at least a bachelor's degree in computer science, mathematics, or a related field. Candidates from India and China working toward permanent residence may also encounter EB-2 or EB-3 immigrant visa petitions filed by larger employers. Australians may find E-3 visas relevant, and Canadians and Mexicans may qualify under TN visa status in computer-related occupations.
Which cities in Connecticut have the most ml engineer sponsorship jobs?
Stamford concentrates the largest share of ml engineer sponsorship activity in Connecticut, driven by its dense cluster of financial services, fintech, and media technology companies. Hartford is the second-largest hub, anchored by insurance carriers and healthcare analytics firms that employ ml engineers for risk modeling and claims automation. New Haven also generates demand through Yale University's research operations and the biotech companies clustered around its medical campus.
How to find ml engineer visa sponsorship jobs in Connecticut?
Migrate Mate filters ml engineer roles specifically by visa sponsorship status and state, making it straightforward to browse open positions in Connecticut without sorting through employers who don't sponsor. The platform surfaces roles from financial services, insurance, and healthcare technology companies, which represent the core of Connecticut's ml engineering market. Searching by city within Connecticut, such as Stamford or Hartford, lets you target the industry clusters most relevant to your background.
Are there state-specific considerations for ml engineers seeking sponsorship in Connecticut?
Connecticut's ml engineering job market skews heavily toward applied machine learning in regulated industries, particularly insurance underwriting, actuarial modeling, and quantitative finance. Employers in these sectors tend to have established legal and HR teams experienced with H-1B sponsorship. Yale University and the University of Connecticut also generate a pipeline of ml talent, which means competition can be meaningful at entry-level positions. Candidates with domain knowledge in financial risk, healthcare data, or natural language processing are particularly well-positioned with Connecticut's dominant employers.
What is the prevailing wage for sponsored ml engineer jobs in Connecticut?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.