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Flexible Remote Machine Learning Engineer Jobs in Springfield, MA

Varsity Tutors

Data Science Tutor

Northampton, MA · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Varsity Tutors

Data Science Tutor

Hartford, CT · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

UnitedHealth Group

Sr Software Engineer

Hartford, CT · Remote

$91K - $163K/yr

... machine learning services/APIs * 1 years of experience with DevOps automation, containerization (Docker, Kubernetes), and CI/CD pipelines (Jenkins, GitHub Actions, GitLab) * 1 years of experience ...

micro1 AI

AI Trainer - Microbiology Expert

Hartford, CT · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Varsity Tutors

Python Tutor

Northampton, MA · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Varsity Tutors

Python Tutor

Hartford, CT · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Cigna

Data Science Advisor - Hybrid

Bloomfield, CT · On-site +1

Strong programming skills in Python, R, SQL, or similar tools. * Hands-on experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch. * Experience developing predictive ...

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Showing results 21-40

All JobsMachine Learning Engineer JobsFlexible Remote Machine Learning Engineer JobsFlexible Remote Machine Learning Engineer Jobs in Springfield, MA

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 Aug 19, 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.

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 are the key skills and qualifications needed to thrive as a flexible remote machine learning engineer?

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.

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 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 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:

Flexible Remote Machine Learning Engineer jobs near you
Infographic showing various Flexible Remote Machine Learning Engineer job openings in Springfield, MA as of August 2026, with employment types broken down into 1% As Needed, 67% Full Time, 29% Part Time, and 3% Contract. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution, with an average salary of $128,319 per year, or $61.7 per hour.

Principal Reliability Engineer - EDS

The Hartford Financial Services Group, Inc.

Hartford, CT • On-site, Remote

Full-time

Re-posted 19 days ago

The Hartford rating

8.8

Company rating: 8.8 out of 10

Based on 121 frontline employees who took The Breakroom Quiz

57th of 310 rated insurance

Job description

Principal Reliability Engineering - IE06JE
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 Enterprise Data Services (EDS) organization is seeking a Principal Reliability Engineer (Principal RE) to serve as the senior technical authority responsible for the reliability, resilience, availability, and performance of all data platforms, cloud infrastructure, data products, and data pipelines across the enterprise data organization. This role sets the strategic vision for Reliability Engineering within EDS and leads the definition, implementation, and continuous evolution of RE practices, tooling, automation, observability frameworks, and AIOps/AI-driven operations.
As the Principal RE, you will influence architectural direction, lead large-scale, cross-organizational technical initiatives, and drive a culture of engineering excellence, automation-first operations, and proactive reliability improvement. You will partner closely with platform engineering, data engineering, security, architecture, and product teams to embed RE principles into every stage of the data product lifecycle.
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).
Key Responsibilities
Enterprise Reliability Strategy & Leadership
  • Work closely with the AVP, RE & Production Support, EDS defining the Reliability Engineering strategy for data platforms, data cloud environments, and data products.
  • Establish long-term RE roadmaps, target operating models, and architectural patterns that scale with organizational growth.
  • Serve as the highest-level technical escalation point for systemic reliability issues, influencing executive stakeholders and engineering leaders.

Platform & Cloud Reliability (AWS, GCP, Snowflake, EMR, Hadoop, ETL/ELT)
  • Leverage Enterprise provided standards and building blocks to Architect and evolve highly reliable, performant, and cost-efficient cloud-based platforms across AWS and GCP for all EDS services.
  • Influence and work directly with Platform Solution Architecture on new product enablement, hyper automation (end to end blueprint automation).
  • Oversee reliability controls and fail-safe patterns for Snowflake, EMR, Hadoop/Spark clusters, container platforms (e.g., Kubernetes), and mission-critical data systems.
  • Lead the creation and enforcement of SLO/SLI frameworks that span the entire data lifecycle.

AI-Enabled Operations, AIOps & Intelligent Automation
  • Develop and implement AI-driven automation for anomaly detection, alert correlation, autonomous remediation, and predictive capacity management.
  • Leverage LLMs, prompt engineering, and cloud-native AI services (AWS Bedrock, SageMaker, Vertex AI) to build intelligent runbooks, advanced troubleshooting agents, and generative-AI-enabled operational tooling.
  • Champion the adoption of machine learning-based observability and reliability analytics.

End-to-End Observability & Operational Excellence
  • Adopt and architect enterprise-wide data observability frameworks-including logging, metrics, tracing, distributed profiling, and event pipelines-for all data platforms and pipelines.
  • Establish gold-standard incident response patterns, post-incident reviews, and continuous improvement processes.
  • Drive elimination of toil across EDS, focusing on self-healing systems, proactive detection, and autonomous operations.

Data Pipeline & Data Product Reliability
  • Define RE best practices for modern data products, governed data pipelines, real-time/streaming systems, and operational analytics platforms.
  • Ensure data quality, data timeliness, and SLAs for data products through automated checks, lineage-informed alerting, and pipeline reliability tooling.
  • Partner with Data Engineering to embed resilience patterns (idempotency, checkpointing, replayability, disaster recovery) into pipeline architectures.

Engineering Standards, Governance & Cross-Org Influence
  • Set and enforce standards for IaC, CI/CD, platform automation, reliability frameworks, operational readiness, and runbook quality across EDS.
  • Provide technical leadership and mentorship to Staff/Senior Engineers in the RE team and Production Support teams, influencing engineering culture and helping grow RE capabilities across the organization.
  • Represent Reliability Engineering in architectural reviews, enterprise governance forums, and executive-level discussions.

Technical Experience
  • 10+ years in one or more of the following areas: data, cloud, platform engineering, site/reliability engineering, or large-scale distributed systems, with experience in leadership or technology leader roles.
  • Proficiency with data or cloud platforms, including architectural patterns for resilience, networking, security, and distributed data infrastructure.
  • Deep experience supporting or engineering platforms such as Snowflake, EMR, Hadoop/Spark, Data Integration, and cloud-native data ecosystems.
  • Scripting and programming (preferably Python) for large-scale automation, platform tooling, and reliability frameworks.
  • Experience with Infrastructure-as-Code (Terraform, CloudFormation) and enterprise CI/CD.

Preferred Qualifications
  • Experience in regulated or highly complex enterprise environments (financial services, insurance, healthcare).
  • Prior experience as a Senior Staff Engineer, Engineering or Architecture leader with hands on experience, or similar senior technical role.
  • Knowledge of data governance, metadata, lineage systems, and data quality engineering practices.
  • Certifications in AWS, GCP, Kubernetes, or SRE/DevOps frameworks.

AI & AIOps
  • Background applying machine learning to operations-anomaly detection, event correlation, predictive modeling, and automated remediation.
  • Understand of AI-enabled developer/operations tools using LLMs, prompt engineering, or cloud AI services for reliability improvements.

Observability & Platform Operations
  • Expertise with enterprise observability stacks (Prometheus, Grafana, Datadog, Splunk, Dynatrace, OpenTelemetry).
  • Ability to design and enforce advanced SLI/SLO frameworks across complex data ecosystems.

Leadership & Cross-Functional Influence
  • Demonstrated ability to lead technical strategy at scale, influence senior engineering leaders, and set enterprise-wide standards.
  • Strong capability in mentoring engineers, providing architectural guidance, and fostering engineering excellence.
  • Exceptional communication skills for interacting with executives, senior architects, product leaders, and engineering teams.

Candidate 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:
$152,800 - $229,200
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

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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