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Machine Learning Engineer Opt Jobs in Hartford, CT

The Hartford is seeking AI Machine Learning Engineer to build Machine Learning Operations (MLOps ... The company will not support the STEM OPT I-983 Training Plan endorsement for this position.

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Senior AI Engineer

Hartford, CT · On-site

$55.75 - $71.75/hr

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 ...

AI Solutions Architect

Hartford, CT · On-site

$63.50 - $83.75/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

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Machine Learning Engineer Opt information

See Hartford, CT salary details

$31.8K

$129.9K

$195.2K

How much do machine learning engineer opt jobs pay per year?

As of Jun 19, 2026, the average yearly pay for machine learning engineer opt in Hartford, CT is $129,891.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,400.00 and $156,400.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What is the difference between Machine Learning Engineer Opt vs Data Scientist?

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

Is a machine learning engineer still in demand?

Yes, machine learning engineers are in high demand due to the growing adoption of AI and data-driven solutions across industries. They are sought after for their skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, and cloud platforms, making this a strong career choice for those with relevant expertise.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances because they develop and refine AI models, requiring specialized skills in programming, data analysis, and domain knowledge. Jobs that involve complex problem-solving, creativity, and emotional intelligence, such as healthcare professionals, educators, and skilled tradespeople, are also expected to persist despite AI automation. Continuous learning and adapting to new tools and technologies will be essential for job security across many fields.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What is a $900,000 AI job?

A $900,000 AI-related job typically refers to high-level roles such as senior machine learning engineers, AI research directors, or chief AI officers, often in large tech companies or specialized firms. These positions usually require advanced skills in machine learning, deep learning, and data science, along with extensive experience and leadership responsibilities.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

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 tech, 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 are popular job titles related to Machine Learning Engineer Opt jobs in Hartford, CT? For Machine Learning Engineer Opt jobs in Hartford, CT, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Opt jobs in Hartford, CT look for? The top searched job categories for Machine Learning Engineer Opt jobs in Hartford, CT are:
What cities near Hartford, CT are hiring for Machine Learning Engineer Opt jobs? Cities near Hartford, CT with the most Machine Learning Engineer Opt job openings:
AI Machine Learning Engineer

$100K - $151K/yr

Full-time

Posted 7 days ago


The Hartford rating

8.8

Company rating: 8.8 out of 10

Based on 104 frontline employees who took The Breakroom Quiz

52nd of 261 rated insurance


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.
The Hartford is seeking 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 Machine Learning AI Engineer, you will play a key role in contributing to the 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.
• Accountable for deployment design, development and maintenance of both traditional ML and AI models.
• 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 cloud environments.
• 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.
• 1+ years of equivalent experience in a research or DevOps function.
• Development experience developing solutions within AWS, GCP or both.
• Exposure to developing repeatable architectural patterns; ability to identify redundancies and eliminate them with these patterns.
• Familiarity with building and deploying API services within the Cloud.
• Familiarity building CICD pipelines using Jenkins or equivalent
• Exposure with IAC (Infrastructure as Code) including Cloud Formation, Terraform, or equivalents
• Experience in Unix, git, and strong object oriented development experience using Python
• Exposure to 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
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

What The Hartford employees say

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Benefits

Hours and flexibility

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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

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