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Embedded Machine Learning Engineer Jobs in Trenton, NJ

Bespoke Labs

Machine Learning Engineer

Trenton, NJ · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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All JobsEmbedded Machine Learning Engineer JobsEmbedded Machine Learning Engineer Jobs in Trenton, NJ

Embedded Machine Learning Engineer information

See Trenton, NJ salary details

$70.2K

$153.8K

$174.5K

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

As of Jul 13, 2026, the average yearly pay for embedded machine learning engineer in Trenton, NJ is $153,806.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,900.00 and $173,500.00 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 are popular job titles related to Embedded Machine Learning Engineer jobs in Trenton, NJ? For Embedded Machine Learning Engineer jobs in Trenton, NJ, the most frequently searched job titles are:
What cities near Trenton, NJ are hiring for Embedded Machine Learning Engineer jobs? Cities near Trenton, NJ with the most Embedded Machine Learning Engineer job openings:
Embedded Machine Learning Engineer jobs near you
Infographic showing various Embedded Machine Learning Engineer job openings in Trenton, NJ 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 $153,806 per year, or $73.9 per hour.
Machine Learning Engineer[C2C/W2 ROLE]

Machine Learning Engineer[C2C/W2 ROLE]

SmartIPlace

Philadelphia, PA • On-site

Contractor

Posted 14 days ago

Job description

Job Title: Machine Learning Engineer [w2 role]

Location: Philadelphia, PA (Onsite – 4 days/week at 1800 Arch Street)
Alternate location: Reston, VA (for strong candidates)
Duration: Contract
Eligibility: USC, GC

Job Summary

We are seeking a hands-on Machine Learning Engineer with 5+ years of experience who can design, build, and deploy scalable machine learning solutions. This role requires strong coding expertise and real-world experience delivering models into production environments. The ideal candidate is not a manager but an individual contributor who thrives in a fast-paced, engineering-focused environment.

Key Responsibilities

  • Model Development: Design, build, train, and fine-tune machine learning and deep learning models for real-world use cases
  • Production Deployment: Deploy, monitor, and maintain ML models in production environments
  • Data Pipeline Development: Build and optimize scalable data pipelines for ingestion, transformation, and processing
  • Performance Optimization: Evaluate models using metrics like accuracy, recall, and AUC; optimize for performance and scalability
  • Collaboration: Work closely with cross-functional teams including data engineers, software engineers, and business stakeholders

Required Skills & Qualifications

  • 5+ years of experience as a Machine Learning Engineer or similar role
  • Strong Python programming skills with solid software engineering fundamentals
  • Recent and hands-on experience with PySpark (mandatory)
  • Experience with machine learning frameworks such as Scikit-learn
  • Strong understanding of statistics, probability, and algorithms
  • Experience working with SQL, data modeling, and large datasets
  • Proven track record of deploying ML models into production environments
  • Experience with AWS services

Preferred Qualifications

  • Experience with MLOps tools such as Docker for model deployment
  • Hands-on experience with local Large Language Models (LLMs)
  • Familiarity with distributed computing and big data technologies

Interview Process

Round 1 (30 mins – Virtual)

  • Experience overview
  • Technical discussion
  • Live coding exercise (Video ON + full desktop screen sharing required)

Round 2 (60 mins – In-Person Preferred)

  • Technical deep dive
  • Advanced live coding exercise

Work Environment

  • 4 days onsite preferred (Philadelphia office)
  • Open to relocation candidates
  • Reston, VA location may be considered if needed
Smart-iPlace logo

About Smart-iPlace

Sourced by ZipRecruiter

SMART-iPLACE provides innovative staffing and consulting solutions that help our clients achieve their business objectives. We can understand and support all areas of your IT systems from back-end infrastructure to front-end personal productivity. Our goal is create innovative IT solutions that enable your business to be more agile and competitive.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Irving, TX, US

Year founded

2021

Social media

Facebook

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