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Hourly Embedded Machine Learning Jobs in Springfield, MA

Deloitte

Cyber - SecOps - Consultant

Hartford, CT · On-site

... machine learning to address cyber-specific challenges. Cyber Detect & Respond practitioners work with clients to modernize large-scale cyber data and analytics programs, support embedded and as-a ...

Ticketnetwork

Director of Data and AI

South Windsor, CT · On-site

... 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

LiquidPiston

CNC Programming Machinist

Suffield, CT · On-site

$20 - $27.25/hr

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

LiquidPiston, Inc.

CNC Programming Machinist

Suffield, CT · On-site

$20 - $27.25/hr

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

TicketNetwork

Director of Data and AI

South Windsor, CT · On-site

... 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

Walmart

DIH O/N Team Associate

Westfield, MA · On-site

$16 - $29/hr

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 ...

CVS Health

AI/LLM Engineer

Hartford, CT · On-site

$101K - $203K/yr

Machine learning concepts (training, evaluation, overfitting, bias) * Practical experience with ... hourly rate or base annual full-time salary for all positions in the job grade within which this ...

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All JobsHourly Embedded Machine Learning JobsHourly Embedded Machine Learning Jobs in Springfield, MA

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 Aug 16, 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:

Hourly Embedded Machine Learning jobs near you
Infographic showing various Hourly Embedded Machine Learning job openings in Springfield, MA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $152,847 per year, or $73.5 per hour.

Cyber - SecOps - Consultant

Deloitte

Hartford, CT • On-site

Full-time

Posted 16 days ago

Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

44th of 150 rated financial services

Job description

If you're looking for an opportunity to work at the intersection of cybersecurity, data, and artificial intelligence, Deloitte's Cyber Defense & Resilience team offers the scale, complexity, and growth environment to build your career. In this role, you will support organizations as they modernize security operations through advanced analytics, cyber data engineering, and AI-enabled capabilities. You will work with leading technologies and help clients strengthen cyber defense while enabling innovation across the enterprise.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Cyber SecOps Consultant on the Cyber Defense & Resilience team, you will be responsible for...

  • Supporting the design and modernization of cyber data and analytics programs that improve organizational intelligence and enable scalable delivery models
  • Developing and applying analytics, machine learning, and data science techniques to cyber use cases across security operations, threat detection, and incident response
  • Working with technologies such as Databricks for Cyber, AWS Security Lake, Google SecOps, Splunk, CrowdStrike, and Palo Alto Networks to support cyber data platforms and operational outcomes
  • Assisting with the maintenance, enhancement, governance, and administration of data platforms and applications using standardized, automated, and AI-enabled DataOps capabilities
  • Contributing to AI and analytics initiatives by helping clients experiment, operationalize, and scale solutions using cyber and information technology telemetry data

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

Cyber Defense & Resilience is an integrated team of security and data technologists working at the intersection of cybersecurity, advanced cyber data engineering, and the use of artificial intelligence and machine learning for cyber defense and operations. The team serves as a trusted advisor and managed service provider, bringing capability and capacity across security data modernization, DataOps, AI, and machine learning to address cyber-specific challenges.

Cyber Detect & Respond practitioners work with clients to modernize large-scale cyber data and analytics programs, support embedded and as-a-service delivery models, and strengthen day-to-day security operations. The team also helps clients harness technologies such as Databricks for Cyber, AWS Security Lake, Google SecOps, Splunk, CrowdStrike, and Palo Alto Networks while advancing AI and analytics capabilities through scalable assets, curated datasets, and operational experience.

Qualifications

Required:

  • 2+ years of analytics consulting or industry experience
  • 2+ years of experience with artificial intelligence development tools, including vector databases such as Pinecone or Elastic, and development frameworks such as LangChain or CrewAI
  • 2+ years of experience in statistical analysis, machine learning, and data mining
  • 2+ years of experience using statistical computer languages such as Python, Structured Query Language (SQL), R, or SAS to prepare data for analysis, perform exploratory analysis, generate features, and support data science workflows
  • 2+ years of experience using cloud-based cybersecurity platforms such as Google SecOps, Amazon Web Services (AWS), or Microsoft Azure
  • 1+ years of experience with security operations center threat hunting and incident response
  • Experience supporting at least one full lifecycle analytics engagement across strategy, design, and implementation
  • Bachelor's degree in Engineering, Mathematics, or Statistics, or 4 years of equivalent professional experience
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Experience architecting, designing, developing, and deploying enterprise data science solutions that include natural language processing (NLP), chatbots, virtual assistants, computer vision, cognitive services, and big data tools used to manage large datasets
  • Experience applying artificial intelligence (AI), machine learning (ML), and advanced data engineering to cybersecurity use cases, including detection and cyber threat response acceleration
  • Experience parsing and normalizing cybersecurity or information technology telemetry datasets
  • Experience using Python machine learning and deep learning frameworks and libraries, including PyTorch, Keras, TensorFlow, scikit-learn, NumPy, and SciPy
  • Experience designing and implementing Apache open-source frameworks, including Kafka, Storm, and Spark, to support end-to-end data management lifecycle activities
  • Experience managing multiple concurrent task assignments and developing presentation materials using Microsoft Visio and Microsoft PowerPoint

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $82,600 - $162,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


Qualifications:

If you're looking for an opportunity to work at the intersection of cybersecurity, data, and artificial intelligence, Deloitte's Cyber Defense & Resilience team offers the scale, complexity, and growth environment to build your career. In this role, you will support organizations as they modernize security operations through advanced analytics, cyber data engineering, and AI-enabled capabilities. You will work with leading technologies and help clients strengthen cyber defense while enabling innovation across the enterprise.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Cyber SecOps Consultant on the Cyber Defense & Resilience team, you will be responsible for...

  • Supporting the design and modernization of cyber data and analytics programs that improve organizational intelligence and enable scalable delivery models
  • Developing and applying analytics, machine learning, and data science techniques to cyber use cases across security operations, threat detection, and incident response
  • Working with technologies such as Databricks for Cyber, AWS Security Lake, Google SecOps, Splunk, CrowdStrike, and Palo Alto Networks to support cyber data platforms and operational outcomes
  • Assisting with the maintenance, enhancement, governance, and administration of data platforms and applications using standardized, automated, and AI-enabled DataOps capabilities
  • Contributing to AI and analytics initiatives by helping clients experiment, operationalize, and scale solutions using cyber and information technology telemetry data

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

Cyber Defense & Resilience is an integrated team of security and data technologists working at the intersection of cybersecurity, advanced cyber data engineering, and the use of artificial intelligence and machine learning for cyber defense and operations. The team serves as a trusted advisor and managed service provider, bringing capability and capacity across security data modernization, DataOps, AI, and machine learning to address cyber-specific challenges.

Cyber Detect & Respond practitioners work with clients to modernize large-scale cyber data and analytics programs, support embedded and as-a-service delivery models, and strengthen day-to-day security operations. The team also helps clients harness technologies such as Databricks for Cyber, AWS Security Lake, Google SecOps, Splunk, CrowdStrike, and Palo Alto Networks while advancing AI and analytics capabilities through scalable assets, curated datasets, and operational experience.

Qualifications

Required:

  • 2+ years of analytics consulting or industry experience
  • 2+ years of experience with artificial intelligence development tools, including vector databases such as Pinecone or Elastic, and development frameworks such as LangChain or CrewAI
  • 2+ years of experience in statistical analysis, machine learning, and data mining
  • 2+ years of experience using statistical computer languages such as Python, Structured Query Language (SQL), R, or SAS to prepare data for analysis, perform exploratory analysis, generate features, and support data science workflows
  • 2+ years of experience using cloud-based cybersecurity platforms such as Google SecOps, Amazon Web Services (AWS), or Microsoft Azure
  • 1+ years of experience with security operations center threat hunting and incident response
  • Experience supporting at least one full lifecycle analytics engagement across strategy, design, and implementation
  • Bachelor's degree in Engineering, Mathematics, or Statistics, or 4 years of equivalent professional experience
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Experience architecting, designing, developing, and deploying enterprise data science solutions that include natural language processing (NLP), chatbots, virtual assistants, computer vision, cognitive services, and big data tools used to manage large datasets
  • Experience applying artificial intelligence (AI), machine learning (ML), and advanced data engineering to cybersecurity use cases, including detection and cyber threat response acceleration
  • Experience parsing and normalizing cybersecurity or information technology telemetry datasets
  • Experience using Python machine learning and deep learning frameworks and libraries, including PyTorch, Keras, TensorFlow, scikit-learn, NumPy, and SciPy
  • Experience designing and implementing Apache open-source frameworks, including Kafka, Storm, and Spark, to support end-to-end data management lifecycle activities
  • Experience managing multiple concurrent task assignments and developing presentation materials using Microsoft Visio and Microsoft PowerPoint

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $82,600 - $162,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


Education:Bachelor's DegreeEmployment Type:

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