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Flexible Remote Machine Learning Engineer Jobs in Springfield, MA

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

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

Provide technical leadership across machine learning, statistical modeling, feature engineering, model evaluation, calibration, explainability, and production-ready analytics. * Drive execution ...

Posted today

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

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Showing results 1-20

Flexible Remote Machine Learning Engineer information

See Springfield, MA salary details

$31.4K

$128.3K

$192.8K

How much do flexible remote machine learning engineer jobs pay per year?

As of Jul 8, 2026, the average yearly pay for flexible remote machine learning engineer in Springfield, MA is $128,319.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,100.00 and $154,500.00 per year, depending on experience, location, and employer.

How does a flexible remote work arrangement impact collaboration and project delivery for Machine Learning Engineers?

In a flexible remote setting, Machine Learning Engineers often rely on digital collaboration tools to communicate with team members and manage projects. This setup allows for asynchronous work, enabling engineers to focus deeply on model development and data analysis without constant interruptions. However, it also means proactively scheduling check-ins and maintaining clear documentation are crucial to ensure alignment across distributed teams. While remote work offers autonomy and work-life balance, successful engineers build strong communication habits to keep projects on track and foster effective collaboration with data scientists, product managers, and software engineers.

What is a Flexible Remote Machine Learning Engineer?

A Flexible Remote Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models while working remotely, often with flexible hours. They use programming, data analysis, and statistical skills to create algorithms that solve real-world problems, collaborating with teams through digital communication tools. This role allows for a better work-life balance and can be performed from anywhere with a reliable internet connection. Flexible remote positions are especially popular in the tech industry, where project-based work and results matter more than strict office hours.

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

AspectFlexible Remote Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, ML, or related fields; experience with ML frameworksBachelor's or higher in CS, Statistics, or related fields; proficiency in data analysis
Work EnvironmentRemote, collaborative teams, project-basedRemote or on-site, data analysis-focused
Industry UsageTech, finance, healthcare, e-commerceTech, marketing, finance, research
Common Search IntentRoles involving ML model development and deploymentRoles focused on data analysis and insights

The main difference is that a Flexible Remote Machine Learning Engineer primarily develops and deploys machine learning models, while a Data Scientist focuses on analyzing data to generate insights. Both roles often require similar educational backgrounds and can be remote, but their core responsibilities differ in application and focus.

What are the key skills and qualifications needed to thrive as a Flexible Remote Machine Learning Engineer, and why are they important?

To thrive as a Flexible Remote Machine Learning Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and typically a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, cloud platforms (AWS, GCP, or Azure), and experience with data pipelines are essential, and certifications in machine learning or cloud technologies can be advantageous. Excellent communication, self-motivation, and time management skills help you collaborate effectively and stay productive in a remote, flexible work environment. These skills ensure you can independently deliver high-quality ML solutions, maintain clear team communication, and adapt to evolving project requirements.
What are popular job titles related to Flexible Remote Machine Learning Engineer jobs in Springfield, MA? For Flexible Remote Machine Learning Engineer jobs in Springfield, MA, the most frequently searched job titles are:
What job categories do people searching Flexible Remote Machine Learning Engineer jobs in Springfield, MA look for? The top searched job categories for Flexible Remote Machine Learning Engineer jobs in Springfield, MA are:
Infographic showing various Flexible Remote Machine Learning Engineer job openings in Springfield, MA as of July 2026, with employment types broken down into 1% Locum Tenens, 93% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $128,319 per year, or $61.7 per hour.
AI Machine Learning Engineer

AI Machine Learning Engineer

The Hartford Financial Services Group, Inc.

Hartford, CT • On-site, Remote

$100K - $151K/yr

Full-time

Posted 26 days ago


The Hartford rating

8.8

Company rating: 8.8 out of 10

Based on 109 frontline employees who took The Breakroom Quiz

51st of 278 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

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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

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