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Remote Embedded Machine Learning Jobs in Westfield, MA

Cyber AI Security Manager

Hartford, CT ยท On-site +1

$112K - $151K/yr

We offer unlimited PTO, a flexible remote work policy, and a supportive environment that ... Act as the security expert in designing, developing, and deploying secure AI and machine learning ...

Showing results 41-51

Remote Embedded Machine Learning information

See Westfield, MA salary details

$73.1K

$160.2K

$181.7K

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

As of Sep 10, 2026, the average yearly pay for remote embedded machine learning in Westfield, MA is $160,157.00, according to ZipRecruiter salary data. Most workers in this role earn between $137,300.00 and $180,600.00 per year, depending on experience, location, and employer.

What is a remote embedded machine learning engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

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

To thrive as a Remote 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 science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

What are some common challenges faced by remote embedded machine learning engineers, and how can they be addressed?

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.

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

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

Research Intern on Generative and Protective AI for Content Creation

Springfield, MA โ€ข On-site, Remote

Sony
Appliances and Electrical and Electronics Wholesalersย โ€ขย 10K+ employees

$50/hr

Full-time

Re-posted 10 days ago


Job description

Sony AI America, a branch of Sony AI, is a remotely distributed organization spread across the U.S. and Canada. Sony AI is Sony's new research organization pursuing the mission to use AI to unleash human creativity. Sony AI works closely with Sony's other business units, including Sony Interactive Entertainment LLC., Sony Pictures Entertainment Inc., and Sony Music Entertainment. With some 900 million Sony devices in hands and homes worldwide today, a vast array of Sony movies, television shows and music, and the PlayStation Network, Sony creates and delivers more entertainment experiences to more people than anyone else on earth. To learn more: https://ai.sony/

Position Summary

Sony AI is seeking research interns who are passionate about ML-based technologies that are useful in movie , game , and music creation, as well as technologies for the ethical operations of generative AIs. Our mission is to research and develop technologies for various Sony Group products and for scientific publication. The technologies developed during the internship will have the potential to be applied in film, game , and music production across entertainment studios worldwide.

Responsibilities

As a research intern, you will investigate and apply novel algorithms related to:

  • The generation and editing of video, sound, and 3D visual geometry (including 3D human motion).
  • The analysis and alleviation of ethical flaws in generative models, including techniques for memorization detection and mitigation, concept erasure, and data attribution.

Your goal will be to publish your findings in a top-tier conference. You are expected to be self-motivated and to implement innovative ideas using your research, coding, and problem-solving skills. You will receive support from internal scientists and engineers in your efforts.

Required Qualifications

  • Master's degree in Computer Science , Electrical Engineering, Applied Mathematics, or related fields.
  • Proven knowledge and expertise in generative AI applications, including deep generative modeling, computer vision, and audio signal processing.
  • Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ).
  • Experience in research communities, including published papers at top-tier conferences such as CVPR, ICCV, ECCV, NeurIPS , ICLR, and ICML.
  • Excellent communication and presentation skills.

Preferred Qualifications

  • Currently enrolled in a relevant Ph.D. program in fields such as Computer Science, Electrical Engineering, Applied Mathematics, or related disciplines.

Working Location

Location flexible (Tokyo, NYC, remote)

The target hourly rate for this internship is $50.00 per hour. The individual will be paid hourly and eligible for overtime .

LI-AS1

All qualified applicants will receive consideration for employment without regard to any basis protected by applicable federal, state, or local law, ordinance, or regulation.

Disability Accommodation for Applicants to Sony Corporation of America Sony Corporation of America provides reasonable accommodation for qualified individuals with disabilities and disabled veterans in job application procedures. For reasonable accommodation requests, please contact us by email at careers@sonyusa.com or by mail to: Sony Corporation of America, People Experience Department, 25 Madison Avenue, New York, NY 10010. Please indicate the position you are applying for.

We are aware that unauthorized individuals or organizations may attempt to solicit personal information or payments from job applicants by impersonating our company through fraudulent job postings. We take these matters seriously but cannot control third-party websites. To protect your personal information, please verify that any job posting you respond to also appears on our official Careers page: www.sonyjobs.com . Please also be advised that we never request personal identifying information (such as Social Security numbers, bank details, or copies of identification documents) during the initial stages of our application process. If you have any doubts about the authenticity of a job posting or communication, please contact careers@sonyusa.com before submitting any information.

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