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Hourly Embedded Machine Learning Jobs in Chicago, IL

Shure

Engineer II, Software

Niles, IL · On-site

$98K - $134K/yr

From developing advanced machine learning models and data-driven systems to optimizing algorithms for deployment across cloud, edge, and embedded platforms, you'll work at the intersection of ...

Shure

Engineer II, Software

Niles, IL · On-site

$98K - $134K/yr

From developing advanced machine learning models and data-driven systems to optimizing algorithms for deployment across cloud, edge, and embedded platforms, you'll work at the intersection of ...

Shure

Engineer II, Software

Niles, IL

$98K - $134K/yr

From developing advanced machine learning models and data-driven systems to optimizing algorithms for deployment across cloud, edge, and embedded platforms, you'll work at the intersection of ...

Shure

Engineer II, Software

Niles, IL · On-site

$98K - $134K/yr

From developing advanced machine learning models and data-driven systems to optimizing algorithms for deployment across cloud, edge, and embedded platforms, you'll work at the intersection of ...

Marmon Holdings, Inc.

Data Scientist

Carol Stream, IL · On-site

What You'll Do * Translate business requirements into analytical, machine learning, and GenAI ... Hands-on usage of Microsoft Copilot tools (e.g., Copilot for M365, Copilot Studio, or embedded ...

Marmon

Data Scientist

Carol Stream, IL · Hybrid

What You'll Do * Translate business requirements into analytical, machine learning, and GenAI ... Handson usage of Microsoft Copilot tools (e.g., Copilot for M365, Copilot Studio, or embedded ...

InRule Technology, Inc.

Senior Data Engineer

Chicago, IL · On-site

$140K - $170K/yr

... machine learning to help IT and business leaders make better decisions faster, operationalize AI ... Develop and optimize reporting and analytics experiences delivered through embedded analytics ...

Aerotek

Machine Operator

Northbrook, IL · On-site

$24.56/hr

... learning machine operation and can apply for the titled Machine Operator role after 90 days, which comes with a higher pay rate. In addition to competitive hourly pay, you receive a gain share bonus ...

Redfish Recruiting

Vision Software

IL · On-site

Understanding of multiples OS's, including Windows, Linux, Windows Embedded, or NI-OS ? Familiarity with machine learning algorithms for vision problems ? Strong personal self-discipline as well as ...

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All JobsHourly Embedded Machine Learning JobsHourly Embedded Machine Learning Jobs in Chicago, IL

Hourly Embedded Machine Learning information

See Chicago, IL salary details

$72.1K

$158K

$179.2K

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

As of Aug 10, 2026, the average yearly pay for hourly embedded machine learning in Chicago, IL is $158,007.00, according to ZipRecruiter salary data. Most workers in this role earn between $135,500.00 and $178,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an hourly embedded machine learning engineer, and why are they important?

To thrive as an Hourly 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 engineering or a related field. Familiarity with tools such as TensorFlow Lite, embedded Linux, microcontroller development environments, and model optimization frameworks is typically required. Strong problem-solving skills, adaptability, and effective communication help you address complex technical challenges and collaborate with cross-functional teams. These skills are crucial for designing efficient, real-time ML solutions that operate reliably on resource-constrained embedded devices.

How does an hourly embedded machine learning professional typically collaborate with hardware and software teams during a project?

As an Hourly Embedded Machine Learning professional, you will often work closely with both hardware and software engineering teams to ensure that machine learning models are efficiently integrated into embedded systems. This typically involves frequent communication to align on hardware constraints, such as memory and processing power, and to optimize algorithms for real-time performance. You may also participate in joint debugging sessions and code reviews to address integration issues and streamline deployment. Collaboration is key, as successful projects depend on the seamless interaction between machine learning solutions and the embedded hardware platform.

What is an hourly embedded machine learning engineer?

An Hourly Embedded Machine Learning engineer is a professional who specializes in developing and deploying machine learning models on embedded systems, such as microcontrollers, IoT devices, or edge devices, and is compensated on an hourly basis rather than a salaried or project-based arrangement. These engineers work to optimize algorithms so they can run efficiently on devices with limited computing power, memory, and energy resources. Their responsibilities often include model selection, quantization, optimization, and integration of machine learning pipelines into hardware. Hiring on an hourly basis allows for flexibility in project scope and duration, making it ideal for companies with specific, time-limited needs. They often collaborate with hardware engineers, data scientists, and software developers to create intelligent embedded solutions.

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

AspectHourly Embedded Machine LearningHourly Data Scientist
CredentialsKnowledge of embedded systems, programming, ML algorithmsDegree in Data Science, Statistics, or related field
Work EnvironmentEmbedded hardware, IoT devices, real-time systemsData analysis, modeling, visualization in office or cloud
Industry UsageConsumer electronics, automotive, IoT devicesFinance, healthcare, marketing, research

Hourly Embedded Machine Learning specialists focus on integrating ML models into embedded systems and hardware, often working with IoT devices and real-time constraints. In contrast, Hourly Data Scientists analyze large datasets to develop predictive models primarily in cloud or office environments. While both roles require programming skills, embedded ML emphasizes hardware integration, whereas data science centers on data analysis and visualization.

What are the most commonly searched types of Embedded Machine Learning jobs in Chicago, IL? The most popular types of Embedded Machine Learning jobs in Chicago, IL are:
What are popular job titles related to Hourly Embedded Machine Learning jobs in Chicago, IL? For Hourly Embedded Machine Learning jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Hourly Embedded Machine Learning jobs in Chicago, IL look for? The top searched job categories for Hourly Embedded Machine Learning jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Hourly Embedded Machine Learning jobs? Cities near Chicago, IL with the most Hourly Embedded Machine Learning job openings:
Hourly Embedded Machine Learning jobs near you

Trading Strategy Software Engineer

BlackEdge Capital

Chicago, IL • On-site, Remote

Full-time

Re-posted 21 days ago

Job description

The Role

BlackEdge Capital is hiring a Trading Strategy Software Engineer to join our technology team and build the systems at the heart of a high frequency, machine learning driven trading effort that operates at the nanosecond level. This is a focused, ambitious initiative at an early stage, which means real ownership and the chance to shape the systems and the codebase from the ground up. Members of our executive team are hands on in this work right now, so you will build alongside the people setting the firm's long-term technical and trading direction.

You will own performance critical software in C++, co-design the hot path with our FPGA hardware engineers, and work shoulder to shoulder with researchers to move machine learning models from idea to live trading. This is a role for someone energized by sitting at the intersection of low-level systems, custom hardware, and applied research, where every nanosecond on the path from signal to order matters.

What You'll Do
  • Design, build, and relentlessly optimize nanosecond level trading systems in C++, owning code from architecture through live production.
  • Partner closely with hardware engineers on FPGA integration, co-designing the software/hardware logic split and communication across that boundary.
  • Work directly with researchers to take machine learning signals from idea to development to production by integrating them into our automated trading system.
  • Keep the codebase clean: we favor a pragmatic, deliberately chosen subset of modern C++ that prioritizes simplicity, clarity, and maintainability.
What We're Looking For
  • Pragmatic C++: Strong command of modern C++ in performance critical systems, with the judgment to keep code simple and clear.
  • Systems depth: Deep understanding of operating system design, cache behavior, memory, and concurrency and how they can be tuned to extract performance.
  • Low latency mindset: A demonstrated ability to design and reason about latency critical software; you think in nanoseconds, not just milliseconds.
  • Collaboration: You enjoy working across boundaries and communicate well with people from diverse backgrounds and skills.
Nice to Have
  • Hands on experience with FPGAs, HLS, or close software/hardware co design.
  • Kernel bypass networking (ef_vi / OpenOnload, DPDK) and low-level network programming.
  • Exposure to machine learning, quantitative research, or production model deployment.
  • Familiarity with futures markets or market microstructure.
About BlackEdge Capital

BlackEdge Capital is a proprietary options market maker built on industry leading technology and a deeply collaborative culture. We compete at the highest technical level in electronic markets, and we win by pairing exceptional engineering with incisive research. Everyone here is a genuine partner in the trading process, embedded in the strategy, close to the technology, and shaping the direction of the firm itself.

How We Work

We are Chicago based and support remote work. We value clarity and simplicity over cleverness for its own sake, tight feedback loops between trading, technology, and operations, and people who take ownership end to end.

Compensation is highly competitive, with significant upside clearly and explicitly tied to firm profit and individual performance. Our model is transparent: bonuses are a share of firm profit, and because your share scales with your performance, a strong year for you and the firm compounds.

Interested? Send us your resume and a short note on where you see yourself contributing at BlackEdge. Humans review every submission.

BlackEdge Capital is an equal opportunity employer. We evaluate candidates on the merit of their work and welcome applicants of every background.

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