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Embedded Machine Learning Jobs in Chicago, IL (NOW HIRING)

Experience applying artificial intelligence, machine learning, or large language model workflows to ... In this embedded, client-facing role, you will work directly with client stakeholders to understand ...

In this embedded, client-facing role, you will work directly with client stakeholders to understand ... Experience applying artificial intelligence, machine learning, or large language model workflows to ...

Senior AI Engineer

Chicago, IL · On-site

$107K - $147K/yr

... innovation, embedded AI capabilities, and global delivery resources-all in service of solving ... The Senior AI Engineer 1 (Senior Staff) leads the development of advanced AI and machine learning ...

Senior AI Engineer

Chicago, IL · On-site +1

$107K - $147K/yr

... innovation, embedded AI capabilities, and global delivery resources-all in service of solving ... The Senior AI Engineer 1 (Senior Staff) leads the development of advanced AI and machine learning ...

Senior AI Engineer

Oakbrook Terrace, IL · On-site +1

$105K - $144K/yr

... innovation, embedded AI capabilities, and global delivery resources-all in service of solving ... The Senior AI Engineer 1 (Senior Staff) leads the development of advanced AI and machine learning ...

... and machine learning, cybersecurity, signals intelligence and more. We can't tell you much more ... Experience in embedded software and/or electrical architecture and development. * Experience in ...

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Embedded Machine Learning information

See Chicago, IL salary details

$72.1K

$158K

$179.2K

How much do embedded machine learning jobs pay per year?

As of Jun 18, 2026, the average yearly pay for 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.

Will AI replace embedded programmers?

Embedded machine learning involves developing algorithms for resource-constrained devices, and while AI tools can assist with coding and optimization, embedded programmers are essential for designing, implementing, and maintaining these systems. AI is more likely to augment their work rather than fully replace them, especially given the need for specialized knowledge of hardware and real-time constraints.

Is embedded AI a good career?

Embedded machine learning involves developing AI models for hardware with limited resources, such as IoT devices and embedded systems. It is a growing field with demand for skills in hardware programming, C/C++, and AI frameworks, offering opportunities in industries like automotive, healthcare, and consumer electronics.

Is embedded systems still a good career in 2026?

Embedded Machine Learning remains a strong career in 2026 as industries increasingly adopt AI-powered devices and IoT solutions. Professionals with skills in hardware programming, real-time systems, and machine learning frameworks like TensorFlow Lite are in demand for developing intelligent embedded applications. Continuous learning and familiarity with microcontrollers, sensors, and embedded software development are essential for long-term growth in this field.

What engineers make $500,000?

Senior engineers in specialized fields such as embedded machine learning, AI, or data science can reach salaries of $500,000 or more, especially with extensive experience, advanced skills in programming and hardware, and leadership roles. High compensation often involves working in high-demand industries, with additional bonuses or stock options contributing to total earnings.

What are some common challenges faced by professionals working in embedded machine learning roles?

Professionals in embedded machine learning roles often face the challenge of optimizing machine learning models to run efficiently on resource-constrained hardware, such as microcontrollers or edge devices with limited memory and processing power. Balancing model accuracy, inference speed, and energy consumption can require creative problem-solving and deep knowledge of both hardware and software. Additionally, collaboration with hardware engineers, data scientists, and software developers is key, as projects typically require cross-functional teamwork to meet performance and deployment goals. Staying current with rapidly evolving tools and best practices is also important in this dynamic field.

What is an Embedded Machine Learning job?

An Embedded Machine Learning job involves developing and optimizing machine learning models to run efficiently on resource-constrained devices like microcontrollers, edge devices, and IoT hardware. Professionals in this role work on model compression, low-power inference, and real-time processing, ensuring AI capabilities can function without relying on cloud computing. Responsibilities often include data preprocessing, feature extraction, model training, and deployment on embedded systems using frameworks like TensorFlow Lite or Edge Impulse.

What are the key skills and qualifications needed to thrive in the Embedded Machine Learning position, and why are they important?

To thrive in Embedded Machine Learning, you should have expertise in machine learning algorithms, embedded systems programming (e.g., C/C++, Python), and a solid understanding of hardware-software integration, typically backed by a degree in computer engineering, electrical engineering, or a related field. Familiarity with edge AI tools (such as TensorFlow Lite, ONNX, or Edge Impulse), microcontrollers, and real-time operating systems is highly valued, alongside relevant certifications such as Embedded Systems or AI certificates. Strong problem-solving skills, effective communication, and the ability to work cross-functionally are crucial soft skills in this field. These qualifications and qualities are vital for creating efficient, reliable AI solutions that operate seamlessly within resource-constrained environments and interdisciplinary project teams.

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:
Infographic showing various Embedded Machine Learning job openings in Chicago, IL as of June 2026, with employment types broken down into 76% Full Time, 7% Part Time, 4% Temporary, 4% Contract, and 9% Nights. Highlights an 91% Physical, 4% Hybrid, and 5% Remote job distribution, with an average salary of $158,007 per year, or $76 per hour.
Senior Director, Revenue Operations

Senior Director, Revenue Operations

Invoca

Chicago, IL

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 28 days ago

Be an early applicant


Job description

About Invoca

Invoca is the industry leader and innovator in AI and machine learning-powered Conversation Intelligence. With over 300 employees, 2,000+ customers, and $100M in revenue, there are tremendous opportunities to continue growing the business. We are building a world-class SaaS company and have raised over $184M from leading venture capitalists, including Upfront Ventures, Accel, Silver Lake Waterman, H.I.G. Growth Partners, and Salesforce Ventures.

About the Team

Our Revenue Operations, Strategy and Enablement organization is designed as a unified, end-to-end revenue engine — aligning Strategy, Operations, Systems, and Enablement across the full customer lifecycle. We have eliminated traditional Sales, Marketing, and Customer Success Ops silos and replaced them with clear ownership across planning, execution, and infrastructure, within our GTM operating model.

The Revenue Operations pillar owns how our revenue engine operates day-to-day. We are the team that translates business needs into operational solutions — defining the processes, workflows, and lifecycle structures that power scalable, efficient GTM execution across Marketing, Sales, and Customer Success.

About the Role

We're seeking a highly operational, process-driven, and strategic Senior Director of Revenue Operations to own end-to-end operational process and procedure design across our full revenue lifecycle. This is not a systems or analytics role — it is a role for someone who excels at translating business needs into operational solutions: defining how the revenue engine runs, how teams collaborate, how workflows are governed, and how the customer journey is operationalized from first touch through retention.

This role will partner closely with our Revenue Systems, Data & AI team to translate operational requirements into scalable system design and implementation, ensuring that what we define operationally is built and embedded into the tech stack. You will manage a cross-functional team covering Marketing Ops, Sales Ops, Customer Success Ops and Customer Education, while personally ensuring CS Ops process design is embedded as a core part of your end-to-end lifecycle ownership.

This role reports to the VP Revenue Operations, Strategy and Enablement, and partners closely across Sales, Marketing, Customer Success, and Finance leadership.

You Will

Own End-to-End Operational Process & Procedure

  • Design and govern GTM operational processes across the full revenue lifecycle — from the first Marketing touch through Customer Success retention
  • Define lifecycle stage definitions, entry/exit criteria, and cross-functional handoff standards, ensuring they are consistently applied and improved over time
  • Govern lead routing, account assignment, territory execution, and workflow design across all GTM functions
  • Own pipeline governance and inspection frameworks in partnership with the Revenue Strategy, Planning & Analytics pillar
  • Identify and systematically eliminate operational friction across the revenue lifecycle

Translate Business Needs into Operational Solutions

  • Act as the primary translator between business strategy and operational execution — defining not just what the goals are, but precisely how teams execute against them
  • Work directly with Sales, Marketing, and CS leadership to understand business needs and design the operational model to support them
  • Partner with Revenue Systems, Data & AI to translate operational requirements into scalable system design and implementation, ensuring what is defined operationally is accurately built into the tech stack
  • Build operational frameworks and documentation that scale with business growth and increasing organizational complexity
  • Ensure that AI and automation investments are grounded in sound operational process design, partnering with Revenue Systems, Data & AI on use case prioritization

Lead and Develop Your Team

  • Lead and develop Revenue Operations Managers covering Marketing Ops and Sales Ops, providing direction, coaching, and clear prioritization
  • Personally own CS Ops process design — including post-sale process optimization, customer health scoring logic, and customer lifecycle communications — as part of your end-to-end lifecycle remit
  • Oversee Customer Education alignment to lifecycle stages, partnering with instructional design and content managers to connect Academy learning pathways to operational lifecycle moments
  • Maintain content and tooling standard alignment between Customer Education and Revenue Training & Enablement

Drive Cross-Functional Alignment & Adoption

  • Serve as the operational liaison across Sales, Marketing, CS, and Finance leadership, representing the operational model and advocating for process integrity
  • Partner with Revenue Strategy, Planning & Analytics on territory execution, pipeline governance, and performance frameworks
  • Align operational workflow rollouts with Revenue Training & Enablement to ensure field readiness and adoption
  • Drive adoption of new processes and workflows across the GTM field, measuring effectiveness and iterating continuously

Continuously Improve the Revenue Engine

  • Bring a data-informed perspective to process improvement, leveraging analytics insights from the Revenue Strategy, Planning & Analytics pillar
  • Continuously evaluate operational processes for efficiency, scalability, and adoption across the field
  • Stay ahead of best practices in revenue operations and bring a clear point of view on how emerging tools and AI capabilities can be operationally embedded
You Have
  • 8–12+ years of experience in Revenue Operations, GTM operations, or closely related roles in B2B SaaS
  • Proven track record designing and governing end-to-end GTM processes across Marketing, Sales, and Customer Success
  • Deep understanding of the full revenue lifecycle and how operational process design drives GTM execution
  • Experience translating business strategy into operational frameworks and procedures
  • Strong partnership experience working with systems/technical teams to translate operational requirements into scalable implementations
  • Experience managing and developing operational teams across multiple GTM functions
  • Demonstrated ability to drive cross-functional alignment across Sales, Marketing, CS, and Finance
  • Strong analytical mindset — able to use data and insights to inform process design and improvement
  • Exceptional communication and stakeholder management skills across all levels of the organization
  • Comfort operating in a fast-moving, high-growth environment where structure is built, not inherited
  • Experience with modern GTM tech stacks (Salesforce, Marketo, Gainsight, Gong, Salesloft) and how system design intersects with operational process
  • Hands-on AI fluency — able to independently build, test, and deploy AI-powered workflows and automations, not just evaluate or direct others to do so; brings both a strategic point of view on where AI applies and the technical capability to prove it out themselves

📍 Location: This is a remote-first role. We are currently hiring in the following locations: 📍

United States: Greater Los Angeles Area (including Santa Barbara and San Diego) · SF Bay Area · Denver Metro · Austin Metro · Chicago Metro · Greater NYC Area
Canada: Toronto (AI/ML technical roles only)
Candidates must be based within ~2 hour drive of these areas. Occasional business travel may be required.

Please note that we are unable to provide initial visa sponsorship for this position.

Salary, Benefits, & Perks

At Invoca, all new hires in the U.S. receive benefits starting on day one of employment. Our benefits offerings include:

Please note that benefits for teammates outside the U.S. may vary in accordance with their country's laws and regulations.

  • Flexible Time Off – We encourage a healthy work-life balance. Our flexible paid time off policy allows you to recharge and take time away as needed.
  • Paid Holidays – Invoca provides 20 U.S. paid holidays, including a winter break, giving you ample opportunity to refresh and spend time with friends and family.
  • Health Benefits – Our healthcare program includes medical, dental, and vision coverage, with multiple plan options to choose what works best for you and your family. Fertility assistance is also included.
  • Retirement – Invoca offers a 401(k) plan through Fidelity with a company match of up to 4%.
  • Stock Options – All employees are invited to share in Invoca's success through stock options.
  • Mental Health Program– Well-being support on a broad range of issues is available through our SpringHealth program.
  • Paid Family Leave – Up to 12 weeks of 100% paid leave is provided for baby bonding, adoption, and caring for family members.
  • Paid Medical Leave – Up to 12 weeks of 100% paid leave is provided for childbirth and medical needs.
  • InVacation – As a thank-you to our long-term team members, we offer a bonus after 7 years of service.
  • Wellness Subsidy – We provide a subsidy that can be applied toward gym memberships, fitness classes, and more.
  • Position Base Range - Salary Range $171,000-$209,000 / plus bonus potential
DEI Statement

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal-opportunity workplace.

#LI-Remote