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Embedded Machine Learning Engineer Jobs (NOW HIRING)

As a Machine Learning Engineer on our core AI/ML team, you will design and build GenAI-powered ... shared AI platform and embedded across products - Design, build, and own end-to-end GenAI ...

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

We are looking for seasoned Machine Learning Engineer to work with our existing team of Data Scientists and Engineers to use AI/ML technology in supporting Federal use cases. We are looking for a ...

Machine Learning Engineer

Mclean, VA · On-site +1

$115K - $150K/yr

We are looking for a more than just a "Machine Learning Engineer", but a technologist with excellent communication and customer service skills and a passion for data and problem solving.

MACHINE LEARNING ENGINEER (MLOPS / DATA ENGINEERING) Overview Darwill is a nationally recognized print and marketing communications firm based in the west suburbs of Chicago. As a premier provider of ...

Machine Learning Engineer We're looking for a talented and motivated Machine Learning Engineer to join our team and help develop cutting-edge AI solutions. In this role, you'll have the opportunity ...

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Embedded Machine Learning Engineer information

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$70K

$153.4K

$174K

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

As of May 30, 2026, the average yearly pay for embedded machine learning engineer in the United States is $153,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,500.00 and $173,000.00 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 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 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 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.

More about Embedded Machine Learning Engineer jobs
What cities are hiring for Embedded Machine Learning Engineer jobs? Cities with the most Embedded Machine Learning Engineer job openings:
What states have the most Embedded Machine Learning Engineer jobs? States with the most job openings for Embedded Machine Learning Engineer jobs include:
Infographic showing various Embedded Machine Learning Engineer job openings in the United States as of May 2026, with employment types broken down into 98% Full Time, 1% Part Time, and 1% Contract. Highlights an 92% Physical, and 8% Remote job distribution, with an average salary of $153,383 per year, or $73.7 per hour.
Machine Learning Engineer

Machine Learning Engineer

Apple

Cupertino, CA

$181.10K - $272.10K/yr

Full-time

Medical, Dental, Retirement

Posted 26 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers


Job description

Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.
Are you an enthusiastic Machine Learning Engineer eager to apply your expertise in a fast-paced, innovative tech environment? Join our Global Sourcing & Supply Management (GSSM) Solutions team as a key player in revolutionizing our supply chain.
As a Machine Learning Engineer on our core AI/ML team, you will design and build GenAI-powered features and workflows leveraging LLMs and modern AI techniques. You will collaborate closely with business stakeholders, product teams, and data engineers to translate complex challenges into practical AI/ML solutions and effectively communicate insights to senior management. Your work will empower data-driven decision-making, optimize workflows, and drive measurable impact across the supply chain.
If you thrive in a collaborative environment, are passionate about applying AI/ML to solve real-world business problems, and are excited to work with cutting-edge GenAI technologies, we want to hear from you!
Description
- Partner with business and product teams to identify high-impact opportunities and translate ambiguous requirements into GenAI-powered features and workflows delivered through a shared AI platform and embedded across products
- Design, build, and own end-to-end GenAI capabilities that support both a centralized AI platform and product teams, covering all aspects from prompt and tool design to agent orchestration, retrieval strategies, model selection, and system evaluation
- Develop reliable, scalable, and cost-aware GenAI features in collaboration with platform, data, and application engineering teams, ensuring strong performance, observability, and maintainability in production environments
- Establish evaluation and monitoring strategies for GenAI-driven features, focusing on output quality, correctness, safety, and business relevance through offline benchmarks, automated checks, and human-in-the-loop review
- Develop Text-to-SQL and structured reasoning capabilities that enable natural-language interaction with structured data, ensuring accuracy, security, and alignment with business semantics
- Leverage agentic AI patterns (multi-step reasoning, tool use, planning, memory, feedback loops) to support complex workflows, while establishing guardrails for reliable and predictable behavior
- Communicate trade-offs, system behavior, and limitations clearly to technical and non-technical stakeholders, enabling informed product and business decisions
- Continuously research, prototype, and operationalize emerging GenAI techniques to improve platform capabilities and accelerate adoption across teams
Preferred Qualifications
Strong problem-solving skills and the ability to tackle ambiguous, real-world challenges, along with clear communication and collaboration skills
Experience with modern deep learning frameworks, such as PyTorch or TensorFlow
Hands-on experience working with transformer-based models, including large language models (e.g., GPT style models or BERT-like architectures)
Practical experience leveraging LLMs or GenAI models via APIs to create reliable and user-facing features or workflows
Familiarity with common GenAI tools and frameworks, such as LangChain or similar, with the ability to learn and adapt as the ecosystem evolves
Solid understanding of foundational ML concepts including supervised, unsupervised and reinforcement learning
Solid understanding of core machine learning concepts, including supervised and unsupervised learning; exposure to reinforcement learning is a plus
Experience with model deployment pipelines and serving GenAI models in production
Experience applying modern ML or GenAI techniques in production workflows, including tasks such as Retrieval-Augmented Generation (RAG), structured reasoning, or prompt-based system design
Experience working in Supply Chain, Operations, or a related field
Ability to operate independently and lead without authority
Minimum Qualifications
Bachelors degree
PhD/MS in Computer Science, Statistics, Applied Math or a related field
5+ years of industry experience
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976