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Embedded Machine Learning Engineer Jobs in Troy, IL

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Implement and deploy machine learning models, working closely with software engineering teams to integrate into customer environments. * Collaborate with subject matter experts to understand ...

Implement and deploy machine learning models, working closely with software engineering teams to integrate into customer environments. * Collaborate with subject matter experts to understand ...

Implement and deploy machine learning models, working closely with software engineering teams to integrate into customer environments. * Collaborate with subject matter experts to understand ...

Implement and deploy machine learning models, working closely with software engineering teams to integrate into customer environments. * Collaborate with subject matter experts to understand ...

Implement and deploy machine learning models, working closely with software engineering teams to integrate into customer environments. * Collaborate with subject matter experts to understand ...

Implement and deploy machine learning models, working closely with software engineering teams to integrate into customer environments. * Collaborate with subject matter experts to understand ...

Hands-on experience with machine learning and AI techniques. * Strong proficiency in SQL and experience working with databases or data warehouses. * Experience with Python, R, or similar programming ...

New

Hands-on experience with machine learning and AI techniques. * Strong proficiency in SQL and experience working with databases or data warehouses. * Experience with Python, R, or similar programming ...

New

Hands-on experience with machine learning and AI techniques. * Strong proficiency in SQL and experience working with databases or data warehouses. * Experience with Python, R, or similar programming ...

New

Implement and deploy machine learning models, working closely with software engineering teams to integrate into customer environments. * Collaborate with subject matter experts to understand ...

Hands-on experience with machine learning and AI techniques. * Strong proficiency in SQL and experience working with databases or data warehouses. * Experience with Python, R, or similar programming ...

New

Hands-on experience with machine learning and AI techniques. * Strong proficiency in SQL and experience working with databases or data warehouses. * Experience with Python, R, or similar programming ...

New

Hands-on experience with machine learning and AI techniques. * Strong proficiency in SQL and experience working with databases or data warehouses. * Experience with Python, R, or similar programming ...

New

Hands-on experience with machine learning and AI techniques. * Strong proficiency in SQL and experience working with databases or data warehouses. * Experience with Python, R, or similar programming ...

New

Hands-on experience with machine learning and AI techniques. * Strong proficiency in SQL and experience working with databases or data warehouses. * Experience with Python, R, or similar programming ...

New

Hands-on experience with machine learning and AI techniques. * Strong proficiency in SQL and experience working with databases or data warehouses. * Experience with Python, R, or similar programming ...

New

Showing results 41-60

Embedded Machine Learning Engineer information

See Troy, IL salary details

$65.2K

$142.9K

$162.1K

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

As of Aug 21, 2026, the average yearly pay for embedded machine learning engineer in Troy, IL is $142,866.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,500.00 and $161,100.00 per year, depending on experience, location, and employer.

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 the key skills and qualifications needed to thrive as an embedded machine learning engineer?

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 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 cities near Troy, IL are hiring for Embedded Machine Learning Engineer jobs?

Cities near Troy, IL with the most Embedded Machine Learning Engineer job openings:

Infographic showing various Embedded Machine Learning Engineer job openings in Troy, IL as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 26% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $142,866 per year, or $68.7 per hour.

Forward Deployed Engineer- AWS

Deloitte

Saint Louis, MO • On-site

Full-time

Re-posted 13 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 151 rated financial services


Job description

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.


Work you'll do

As an AWS AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:


Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.


Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.


Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 3+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with AWS AI&Data including hands on experience with one of the following key platforms/products: Amazon Bedrock, Bedrock AgentCore, Strands Agents SDK, Knowledge Bases, Guardrails
  • 1+ years of experience with AWS Neptune and OpenSearch
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • At least 3 of 6 certifications from the following list: AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate)
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • 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 qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience with SageMaker fine-tuning (SFT and RFT) for domain SLMs
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations


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 $134,500 to $265,100.


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:

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.


Work you'll do

As an AWS AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:


Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.


Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.


Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 3+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with AWS AI&Data including hands on experience with one of the following key platforms/products: Amazon Bedrock, Bedrock AgentCore, Strands Agents SDK, Knowledge Bases, Guardrails
  • 1+ years of experience with AWS Neptune and OpenSearch
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • At least 3 of 6 certifications from the following list: AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate)
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • 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 qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience with SageMaker fine-tuning (SFT and RFT) for domain SLMs
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations


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 $134,500 to $265,100.


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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