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Embedded Machine Learning Engineer Jobs in New Jersey

Lead, Machine Learning Engineer

Newark, NJ · On-site

$107K - $141K/yr

As a Lead, Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals to implement machine learning models that will deliver stability ...

Sr Machine Learning Engineer

Piscataway, NJ

$55.75 - $73.75/hr

Machine Learning Engineer / Architect Experience • 7+ years' experience in designing and developing enterprise class AI Platforms and solutions • 3+ years of experience with enterprise fully ...

We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer vision and AI solutions. You will work on projects involving image capture , data extraction , and ...

We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer vision and AI solutions. You will work on projects involving image capture , data extraction , and ...

We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer vision and AI solutions. You will work on projects involving image capture , data extraction , and ...

We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer vision and AI solutions. You will work on projects involving image capture , data extraction , and ...

Partner with executive leadership, engineering, product, and data science teams to ensure AI ... Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience ...

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Embedded Machine Learning Engineer information

See New Jersey salary details

$71.1K

$155.7K

$176.7K

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

As of Jun 14, 2026, the average yearly pay for embedded machine learning engineer in New Jersey is $155,720.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $175,600.00 per year, depending on experience, location, and employer.

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

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What does an Embedded Machine Learning Engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

What are some common challenges faced by Embedded Machine Learning Engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

What is the difference between Embedded Machine Learning Engineer vs Firmware Engineer?

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

What job categories do people searching Embedded Machine Learning Engineer jobs in New Jersey look for? The top searched job categories for Embedded Machine Learning Engineer jobs in New Jersey are:
What cities in New Jersey are hiring for Embedded Machine Learning Engineer jobs? Cities in New Jersey with the most Embedded Machine Learning Engineer job openings:
Lead, Machine Learning Engineer

Lead, Machine Learning Engineer

Prudential

Newark, NJ • On-site

$107K - $141K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago


Prudential rating

8.6

Company rating: 8.6 out of 10

Based on 43 frontline employees who took The Breakroom Quiz

74th of 261 rated insurance


Job description

Job Classification:

Technology - Data Analytics & Management

Are you interested in building capabilities that enable the organization with innovation, speed, agility, scalability and efficiency? The Global Technology team takes great pride in our culture where digital transformation is built into our DNA! When you join our organization at Prudential, you'll unlock an exciting and impactful career - all while growing your skills and advancing your profession at one of the world's leading financial services institutions.

As a Lead, Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals to implement machine learning models that will deliver stability, producibility, scalability and integration with other products and services. You will implement capabilities to solve sophisticated business problems, deploy innovative products, services and experiences to delight our customers! In addition to advanced technical expertise and experience, you will bring excellent problem solving, communication and teamwork skills, along with agile ways of working, strong business insight, an inclusive leadership attitude and a continuous learning focus to all that you do.

Here is what you can expect in a typical day:

  • Operationalize ML software models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams; remove complex technical impediments
  • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
  • Leverage cloud-based architectures and technologies to deliver optimized ML models at scale
  • Construct optimized data pipelines to feed ML models
  • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code
  • Bring a strong understanding of relevant and emerging technologies, provide input and coach team members and embed learning and innovation in the day-to-day
  • Work on complex problems in which analysis of situations or data requires an evaluation of intangible variables.
  • Use programming languages including but not limited to Python, R, SQL, Java or Scala, SQL

The Skills and expertise you bring:

  • Bachelor of Computer Science or Engineering or experience in related fields
  • Ability to coach others with minimal guidance and effectively leverage diverse ideas, experiences, thoughts and perspectives to the benefit of the organization
  • Experience with agile development methodologies and Test-Driven Development (TDD)
  • Knowledge of business concepts, tools and processes that are needed for making sound decisions in the context of the company's business
  • Ability to learn new skills and knowledge on an on-going basis through self-initiative and tackling challenges
  • Excellent problem solving, communication and collaboration skills

Advanced experience and/or expertise with several of the following:

  • Software Engineering & System Design: Requirement analysis, coding, and testing, version control, microservices architecture, building RestFul APIs, Distributed computing, architecture patterns, general understanding of computer architecture, Object-oriented programming concepts
  • Machine Learning and Deep Learning: Good understanding of: ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikit-learn etc., Neural network, NLP, computer vision, and predictive analytics
  • Model Performance Management: model monitoring, model validation, bias detection, explainability, performance, drift, outliers etc.
  • Model Deployment: Thorough Understanding of MDLC (Model Development Life Cycle), CI/CD/CT pipelines (using tools like Jenkins, CloudBees, Harness etc.), A/B testing. Pipeline frameworks like MLFlow, AWS SageMaker pipeline etc. model and data versioning
  • Data Integration, Transformation & Processing: Transforming and mapping raw data to generate insights. Data wrangling through various tools. Understanding big data ecosystems, relational, NOSQL and graph databases, unstructured and semi-structured data. Data processing on distributed systems with Spark/PySpark
  • Statistics and Computing: Strong knowledge of: Linear Algebra, Probability and Statistics, Multivariate Calculus, Distributions like Poisson, Normal, Binomial etc.
  • Programming Languages: Python, R, SQL, Java or Scala, SQL
You'll Love Working Here Because You Can

Join a team and culture where your voice matters; where every day, your work transforms our experiences to make lives better. As you put your skills to use, we'll help you make an even bigger impact with learning experiences that can grow your technical AND leadership capabilities. You'll be surprised by what this rock-solid organization has in store for you.

What we offer you:Prudential is required by state specific laws to include the salary range for this role when hiring a resident in applicable locations. The salary range for this role is from $125,000.00 to $229,700.00. Specific pricing for the role may vary within the above range based on many factors including geographic location, candidate experience, and skills.
  • Market competitive base salaries, with a yearly bonus potential at every level.

  • Medical, dental, vision, life insurance, disability insurance, Paid Time Off (PTO), and leave of absences, such as parental and military leave.

  • 401(k) plan with company match (up to 4%).

  • Company-funded pension plan.

  • Wellness Programs including up to $1,600 a year for reimbursement of items purchased to support personal wellbeing needs.

  • Work/Life Resources to help support topics such as parenting, housing, senior care, finances, pets, legal matters, education, emotional and mental health, and career development.

  • Education Benefit to help finance traditional college enrollment toward obtaining an approved degree and many accredited certificate programs.

  • Employee Stock Purchase Plan: Shares can be purchased at 85% of the lower of two prices (Beginning or End of the purchase period), after one year of service.

Eligibility to participate in a discretionary annual incentive program is subject to the rules governing the program, whereby an award, if any, depends on various factors including, without limitation, individual and organizational performance. To find out more about our Total Rewards package, visit Work Life Balance | Prudential Careers. Some of the above benefits may not apply to part-time employees scheduled to work less than 20 hours per week.

Prudential Financial, Inc. of the United States is not affiliated with Prudential plc. which is headquartered in the United Kingdom.

Prudential is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender identity, national origin, genetics, disability, marital status, age, veteran status, domestic partner status, medical condition or any other characteristic protected by law.

If you need an accommodation to complete the application process, please email accommodations.hw@prudential.com.

If you are experiencing a technical issue with your application or an assessment, please email careers.technicalsupport@prudential.com to request assistance.


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