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Founding Machine Learning Engineer Jobs in Naperville, IL

IMC

Hardware Machine Learning Engineer

Chicago, IL

$127K - $167K/yr

... engineers to implement, verify, and deploy ML inference solutions from proof-of-concept through production * Track and evaluate emerging research in neural architecture search, machine learning ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

... engineers to implement, verify, and deploy ML inference solutions from proof-of-concept through production * Track and evaluate emerging research in neural architecture search, machine learning ...

PayPal, Inc.

Sr Machine Learning Engineer

Chicago, IL · On-site

$57.50 - $76/hr

D.) in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, or a related field. * Strong knowledge of statistical and machine learning techniques, including but ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

... engineers to implement, verify, and deploy ML inference solutions from proof-of-concept through production * Track and evaluate emerging research in neural architecture search, machine learning ...

PayPal

Sr Machine Learning Engineer

Chicago, IL

$57.50 - $76/hr

D.) in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, or a related field. * Strong knowledge of statistical and machine learning techniques, including but ...

The Hartford

Sr AI Machine Learning Engineer

Chicago, IL · Hybrid

$117K - $175K/yr

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team. The Hartford is developing industryleading ...

PayPal

Staff Machine Learning Engineer

Chicago, IL · Hybrid

$169K - $291K/yr

... machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML ...

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All JobsFounding Machine Learning Engineer JobsFounding Machine Learning Engineer Jobs in Naperville, IL

Founding Machine Learning Engineer information

See Naperville, IL salary details

$31.5K

$128.6K

$193.2K

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

As of Jul 14, 2026, the average yearly pay for founding machine learning engineer in Naperville, IL is $128,577.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,300.00 and $154,800.00 per year, depending on experience, location, and employer.

What is a Founding Machine Learning Engineer?

A Founding Machine Learning Engineer is one of the first technical team members at a startup who specializes in designing, building, and deploying machine learning systems. This role involves working closely with the founders to set the technical direction, build core AI products, and establish best practices for data and model development. In addition to hands-on coding and experimentation, a Founding Machine Learning Engineer often influences product decisions and helps shape the company's engineering culture. The role typically requires a blend of deep technical expertise, startup agility, and a willingness to tackle both high-level strategy and low-level engineering tasks.

What engineer makes $500,000 a year?

A founding machine learning engineer at top tech companies or successful startups can earn $500,000 or more annually, often including base salary, bonuses, and equity. Such roles typically require advanced skills in deep learning, data modeling, and experience with large-scale systems, along with a strong track record of innovation and leadership.

What are some unique challenges and expectations for a Founding Machine Learning Engineer in an early-stage startup?

As a Founding Machine Learning Engineer, you'll face the unique challenge of building the company's machine learning infrastructure from the ground up, often with limited resources and rapidly evolving requirements. You'll be expected to wear many hats, from designing and deploying models to setting up data pipelines and collaborating closely with product and engineering teams. Your role will also involve making critical decisions about technology stacks and best practices that will shape the company's technical direction. Additionally, you'll have significant influence on the company's culture and have ample opportunities for growth as the team expands.

What is a founding ML engineer?

A founding machine learning engineer is a key technical team member involved in building and developing the company's initial machine learning systems and infrastructure. They typically have strong skills in programming, data modeling, and deploying ML models, often working closely with product teams during the startup or early-stage company formation. This role requires a combination of technical expertise and entrepreneurial mindset to shape the company's AI capabilities from the ground up.

Is a machine learning engineer still in demand?

Yes, machine learning engineers are in high demand due to the increasing adoption of AI and data-driven solutions across industries. They are sought after for their skills in algorithms, programming, and tools like Python and TensorFlow, with job growth expected to continue as AI applications expand.

Which 5 jobs will survive AI?

Founding Machine Learning Engineers are likely to continue playing a crucial role as AI advances, focusing on developing and deploying complex models that require specialized skills in programming, data science, and system architecture. Jobs that involve high levels of creativity, strategic decision-making, and human interaction—such as healthcare professionals, educators, skilled trades, and roles in management—are also expected to persist despite AI automation. These positions typically require emotional intelligence, critical thinking, and adaptability that AI cannot easily replicate.

What are the key skills and qualifications needed to thrive as a Founding Machine Learning Engineer, and why are they important?

To thrive as a Founding Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, and data science, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and experience deploying ML models in production are typically required. Strong problem-solving abilities, entrepreneurial mindset, and excellent communication skills set standout candidates apart. These skills and qualities are vital for driving innovation, building scalable solutions from scratch, and collaborating within a fast-paced startup environment.
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Founding Machine Learning Engineer jobs near you
Hardware Machine Learning Engineer

Hardware Machine Learning Engineer

IMC

Chicago, IL

$127K - $167K/yr

Other

Re-posted 29 days ago

Job description

We are deploying machine learning directly onto custom hardware - and we want you to help drive it from the ground up. This is an initiative where you'll have the rare opportunity to architect solutions from scratch, influence technical research direction, and see your work drive real impact in one of the most demanding computing environments in the world.

We build the hardware, the software, and the infrastructure, so when you hit a bottleneck, you can fix it - there's no vendor to wait on and no abstraction layer you're not allowed to touch. If you've ever wanted to push the boundaries of what's computationally possible, this role is for you. We're looking for researchers and experienced engineers from any background. Trading experience is a bonus, not a prerequisite.

Your Core Responsibilities

  • Architect and co-design ML models with traders, quant researchers, and software engineers, treating hardware constraints (latency budgets, resource limits, numerical precision) as first-class design inputs
  • Shape our custom hardware roadmap by translating ML model requirements into concrete architectural decisions
  • Work hands-on with hardware engineers to implement, verify, and deploy ML inference solutions from proof-of-concept through production
  • Track and evaluate emerging research in neural architecture search, machine learning systems and quantization methods, and determine what translates to measurable improvements in our systems

Your Skills and Experience

  • Solid understanding of hardware constraints and design trade-offs (e.g., pipelining, resource utilization, fixed-point arithmetic) that shape how ML models can be efficiently mapped onto FPGAs or custom ASICs
  • Experience with hardware fundamentals, whether through VHDL/SystemVerilog development, HLS tools, or ML-to-hardware frameworks like hls4ml, FINN, or Vitis AI
  • Understanding of machine learning fundamentals - neural network architectures, inference optimization, quantization techniques, ML frameworks such as PyTorch/TensorFlow
  • Proficiency in Python, C++, or similar languages for tooling, testing, and simulation
  • Strong communication skills and ability to work collaboratively across disciplines with both technical and non-technical teams

Nice to Have

  • Exposure to ML compiler infrastructure such as MLIR, TVM, XLA, or similar tools for lowering and optimizing models for hardware targets
  • Background in latency-sensitive or resource-constrained systems including high-frequency trading, particle physics data acquisition, real-time signal processing, or similar domains
  • Familiarity with functional verification methodologies (for example SystemVerilog, UVM, Cocotb)
  • Advanced degree (MS or PhD) in EE, CS, Physics, or related field, or equivalent depth through industry or research experience

Apply