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Machine Learning Engineer Jobs in Springfield, MA

The role involves building, training, validating, and deploying machine learning models, as well as ... Data Engineering Skills • Expertise in Statistics and Analytical Skills • Intermediate ...

Lead AI Engineer

Springfield, MA · On-site

$172K - $225K/yr

Deep expertise in machine learning, statistics, NLP, and LLMs , including generative AI, agentic architectures, prompt engineering, and LLM evaluation across a variety of foundation models and ...

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Showing results 41-60

Machine Learning Engineer information

See Springfield, MA salary details

$31.4K

$128.2K

$192.6K

How much do machine learning engineer jobs pay per year?

As of Sep 8, 2026, the average yearly pay for machine learning engineer in Springfield, MA is $128,195.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,000.00 and $154,300.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

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 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 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.

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.

What are popular job titles related to Machine Learning Engineer jobs in Springfield, MA?

For Machine Learning Engineer jobs in Springfield, MA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer jobs in Springfield, MA look for?

The top searched job categories for Machine Learning Engineer jobs in Springfield, MA are:

What cities near Springfield, MA are hiring for Machine Learning Engineer jobs?

Cities near Springfield, MA with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Springfield, MA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $128,195 per year, or $61.6 per hour.

AVP, AI (Data Science/Engineer) Remote - EST

Hartford, CT • Remote

$185K - $235K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 13 days ago


Job description

With a company culture rooted in collaboration, expertise and innovation, we aim to promote progress and inspire our clients, employees, investors and communities to achieve their greatest potential. Our work is the catalyst that helps others achieve their goals. In short, We Enable Possibility.

Strategic Analytics is a dynamic and growing team at Arch that drives innovation and transforms how the business operates. We build AI-first, agent-driven products that change how Arch underwrites, services, and learns from its book, combining frontier LLMs, multi-agent systems, retrieval-augmented generation (RAG), evaluation frameworks, and traditional machine learning.Our mission spans agentic automation, decision intelligence, AI-driven insights, and the responsible deployment of AI at scale. With a proven track record of productionizing dozens of high-quality GenAI products over the past three years, we are continuing to scale our impact and are seeking an AVP, AI Engineering to lead the design and application of advanced AI systems within Strategic Analytics.

Reporting to the SVP of AI & Automation, you will lead the development of multi-agent AI solutions that automate complex business decisions across underwriting and claims. This role is focused on applying AI, machine learning, and data science to solve high-value business problems, establish decision frameworks, and ensure AI systems deliver measurable outcomes with high levels of accuracy and trustworthiness.

Key Responsibilities

Lead the design of multi-agent AI systems that coordinate specialized models and agents to solve complex business problems.

Drive the end-to-end delivery of AI-powered underwriting and claims solutions from experimentation through production deployment.

Develop and evaluate decision frameworks that combine LLMs, retrieval systems, machine learning models, business rules, and human review.

Establish methodologies for measuring model performance, calibration, confidence, accuracy, and business impact to determine when automation is appropriate.

Define the conditions under which AI-driven decisions should be trusted, reviewed, or escalated.

Partner with cross-functional teams to integrate AI capabilities into business workflows and operational processes.

Mentor data scientists, AI engineers, and analysts on agentic AI, model evaluation, prompt engineering, and responsible AI practices.

Establish standards for AI evaluation, monitoring, governance, and continuous improvement within the AI & Automation Center of Excellence.

Translate business opportunities into scalable AI solutions that deliver measurable business value.

Required Skills and Experience

7+ years of experience in AI, machine learning, data science, analytics, or related disciplines.

3+ years of people leadership experience.

Demonstrated experience building and deploying production-grade AI, machine learning, or agentic systems beyond proof-of-concept work.

Strong track record of developing supervised learning models (ML and/or GLMs) that have delivered measurable financial impact.

Deep understanding of model evaluation, experimentation, statistical analysis, and decision science.

Strong experience evaluating AI technologies, platforms, and vendors.

Strong Python experience for data science, machine learning, and AI development.

Exceptional problem-solving skills with the ability to frame ambiguous business challenges as analytical and AI opportunities.

Strong communication skills with the ability to influence technical and non-technical stakeholders.

Hands-on experience with modern AI technologies, including LLMs, RAG, agentic systems, evaluation frameworks, and emerging AI tooling.

Desired Skills and Experience

Familiarity with P&C insurance, including underwriting, claims, or the submission lifecycle.

Experience with retrieval-augmented generation (RAG), evaluation frameworks, and structured-output techniques.

Experience applying AI and machine learning within enterprise environments.

Experience leading multidisciplinary teams across data science, AI, analytics, and technology functions.

Demonstrated commitment to staying current with advancements in AI through research, experimentation, publications, conference participation, or contributions to the AI community.

Education

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Analytics, or equivalent practical experience.

#LI-LH1

#LI-REMOTE

For individuals assigned or hired to work in the location(s) indicated below, the base salary range is provided. Range is as of the time of posting. Position is incentive eligible.

$185,000 - $235,000/year

  • Total individual compensation (base salary, short & long-term incentives) offered will take into account a number of factors including but not limited to geographic location, scope & responsibilities of the role, qualifications, talent availability & specialization as well as business needs. The above pay range may be modified in the future.

  • Arch is committed to helping employees succeed through our comprehensive benefits package that includes multiple medical plans plus dental, vision and prescription drug coverage; a competitive 401k with generous matching; PTO beginning at 20 days per year; up to 12 paid company holidays per year plus 2 paid days of Volunteer Time Offer; basic Life and AD&D Insurance as well as Short and Long-Term Disability; Paid Parental Leave of up to 10 weeks; Student Loan Assistance and Tuition Reimbursement, Backup Child and Elder Care; and more. Click here to learn more on available benefits.

Do you like solving complex business problems, working with talented colleagues and have an innovative mindset? Arch may be a great fit for you.If this job isn't the right fit but you're interested in working for Arch, create a job alert! Simply create an account and opt in to receive emails when we have job openings that meet your criteria. Join our talent community to share your preferences directly with Arch's Talent Acquisition team.

10200 Arch Capital Services LLC