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Hourly Embedded Machine Learning Jobs in Springfield, MA

... embedded into core claim processes and colleague experiences. * Build deep partnerships within ... Master's or Ph.D. preferred in Machine Learning, Data Science, Computer Science, Applied ...

... embedded into systems and workflows, preventing bad data at the source rather than correcting it ... Generative AI, machine learning, and advanced analytics * Enterprise data and analytics platforms

CNC Programmer/Prototype Machinist

Suffield, CT · On-site

$25.75 - $35.25/hr

Hourly About LiquidPiston: LiquidPiston is developing advanced rotary engine technologies that ... Operate manual machine tools, including: * Surface grinder * Bridgeport mill * Manual lathe

PM Mechanic

Bloomfield, CT

$27.35 - $36.23/hr

PM Mechanic Performs preventative and predictive maintenance on facility machinery. Essential ... Seeks to develop technical knowledge through learning from other experts * Understands ...

New

The actual hourly rate will equal or exceed the required minimum wage applicable to the job ... Ability to operate heavy machinery such as forklifts may also be necessary. Benefits & perks At ...

The actual hourly rate will equal or exceed the required minimum wage applicable to the job ... Ability to operate heavy machinery such as forklifts may also be necessary. Benefits & perks At ...

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Hourly Embedded Machine Learning information

See Springfield, MA salary details

$69.8K

$152.8K

$173.4K

How much do hourly embedded machine learning jobs pay per year?

As of Jul 18, 2026, the average yearly pay for hourly embedded machine learning in Springfield, MA is $152,847.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,000.00 and $172,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Hourly Embedded Machine Learning Engineer, and why are they important?

To thrive as an Hourly Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer engineering or a related field. Familiarity with tools such as TensorFlow Lite, embedded Linux, microcontroller development environments, and model optimization frameworks is typically required. Strong problem-solving skills, adaptability, and effective communication help you address complex technical challenges and collaborate with cross-functional teams. These skills are crucial for designing efficient, real-time ML solutions that operate reliably on resource-constrained embedded devices.

How does an Hourly Embedded Machine Learning professional typically collaborate with hardware and software teams during a project?

As an Hourly Embedded Machine Learning professional, you will often work closely with both hardware and software engineering teams to ensure that machine learning models are efficiently integrated into embedded systems. This typically involves frequent communication to align on hardware constraints, such as memory and processing power, and to optimize algorithms for real-time performance. You may also participate in joint debugging sessions and code reviews to address integration issues and streamline deployment. Collaboration is key, as successful projects depend on the seamless interaction between machine learning solutions and the embedded hardware platform.

What is an Hourly Embedded Machine Learning engineer?

An Hourly Embedded Machine Learning engineer is a professional who specializes in developing and deploying machine learning models on embedded systems, such as microcontrollers, IoT devices, or edge devices, and is compensated on an hourly basis rather than a salaried or project-based arrangement. These engineers work to optimize algorithms so they can run efficiently on devices with limited computing power, memory, and energy resources. Their responsibilities often include model selection, quantization, optimization, and integration of machine learning pipelines into hardware. Hiring on an hourly basis allows for flexibility in project scope and duration, making it ideal for companies with specific, time-limited needs. They often collaborate with hardware engineers, data scientists, and software developers to create intelligent embedded solutions.

What is the difference between Hourly Embedded Machine Learning vs Hourly Data Scientist?

AspectHourly Embedded Machine LearningHourly Data Scientist
CredentialsKnowledge of embedded systems, programming, ML algorithmsDegree in Data Science, Statistics, or related field
Work EnvironmentEmbedded hardware, IoT devices, real-time systemsData analysis, modeling, visualization in office or cloud
Industry UsageConsumer electronics, automotive, IoT devicesFinance, healthcare, marketing, research

Hourly Embedded Machine Learning specialists focus on integrating ML models into embedded systems and hardware, often working with IoT devices and real-time constraints. In contrast, Hourly Data Scientists analyze large datasets to develop predictive models primarily in cloud or office environments. While both roles require programming skills, embedded ML emphasizes hardware integration, whereas data science centers on data analysis and visualization.

What job categories do people searching Hourly Embedded Machine Learning jobs in Springfield, MA look for? The top searched job categories for Hourly Embedded Machine Learning jobs in Springfield, MA are:
What cities near Springfield, MA are hiring for Hourly Embedded Machine Learning jobs? Cities near Springfield, MA with the most Hourly Embedded Machine Learning job openings:
Infographic showing various Hourly Embedded Machine Learning job openings in Springfield, MA as of July 2026, with employment types broken down into 1% Internship, 92% Full Time, 5% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $152,847 per year, or $73.5 per hour.
ASE Methods - Data Science & Analytics Principal Engineer (Onsite)

ASE Methods - Data Science & Analytics Principal Engineer (Onsite)

Raytheon Technologies

East Hartford, CT • On-site

$112K - $135K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 14 hours ago


Job description

Date Posted:
2026-05-19
Country:
United States of America
Location:
US-CT-EAST HARTFORD-ETC ~ 400 Main St ~ BLDG ETC
Position Role Type:
Remote
U.S. Citizen, U.S. Person, or Immigration Status Requirements:
U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract.
Security Clearance Type:
None/Not Required
Security Clearance Status:
Not Required
At RTX, the world largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world.
Pratt & Whitney is a world leader in the design, manufacture and service of aircraft engines and auxiliary power systems and has been revolutionizing modern flight for over 100 years. Join us and help shape the future of aerospace and defense.
Aftermarket & Sustainment Engineering (ASE), based in East Hartford Connecticut, is looking for a Data Science & Analytics expert to join our team.
This role will be responsible for the development, deployment, and support of game-changing machine learning and statistical models that provide forecasting, prediction and prescriptive solutions that can be embedded into our software and workflows. In this role, you'll also perform analytical studies to provide business insight and enable better data-based decisions. These solutions will enable Pratt & Whitney to continually push the state of the art in gas turbine engine repairs and reduce the cost of maintaining our parts, components, and engines.
What You Will Do :
  • Leverage ASE's aftermarket data to provide insights and better decision making
  • Define, prototype, test, deploy and monitor machine learning and statistical models to provide predictions and forecasts
  • Build Power BI dashboards
  • Mentor and train less experienced team members
  • Understand, explain, and recommend appropriate Machine Learning/Data Analytics methods and software solutions
  • Work with the app development team to integrate predictive and prescriptive models into our tools
  • Collaborate with other team members and stakeholders to identify improvement opportunities
  • Manage time effectively to meet project deadlines

What You Will Learn:
  • Experience building end-to-end machine learning solutions
  • Advanced skills with modern data engineering and analytics platforms
  • Practical expertise in applying statistical and ML techniques to real business problems
  • Agile and iterative development practices
  • Software integration and cross-functional collaboration

Qualifications You Must Have:
  • Bachelor's degree in Data Science, Engineering, Software Engineering or Computer Science with 8+ years' experience or a advanced degree with a minimum of 5 years of experience
  • 3+ years' of experience building machine learning/statistical models
  • 3+ years' of experience developing in Python
  • 10% Travel

Qualifications We Prefer:
  • Experience with Databricks
  • Experience developing PowerBI/Qlik dashboards
  • Experience working in an agile environment

Learn More & Apply Now!
What is my role type?
In addition to transforming the future of flight, we are also transforming how and where we work. We've introduced role types to help you understand how you will operate in our blended work environment. This role is:
Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance workers, as they are essential to the development of our engines.
Candidates will learn more about role type and current site status throughout the recruiting process. For onsite and hybrid roles, commuting to and from the assigned site is the employee's personal responsibility.
As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote.
The salary range for this role is 107,500 USD - 204,500 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills.
Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement.
Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance.
This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply.
RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window.
RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act.
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