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Software Engineer Ml Jobs in Chicago, IL (NOW HIRING)

Familiarity with AI/ML systems is a plus but not required. * Experience with rigorous code reviews and software engineering best practices . * Experience working effectively in remote or cross ...

Partner with data scientists and ML engineers to turn prototypes into maintainable software. * Contribute to architecture decisions, code reviews, testing strategy and engineering standards. Who are ...

Sr. Software Engineer

Chicago, IL · On-site

$130K - $140K/yr

Partner with data scientists and ML engineers to turn prototypes into maintainable software. * Contribute to architecture decisions, code reviews, testing strategy and engineering standards. Who are ...

Partner with data scientists and ML engineers to turn prototypes into maintainable software. * Contribute to architecture decisions, code reviews, testing strategy and engineering standards. You are ...

Software Engineer

Oak Brook, IL · On-site

$90K - $120K/yr

Software Engineer Job Overview: We are seeking a Python Senior Software Engineers to build and ... Experience with AI/ML, OCR, and cloud platforms (especially Azure) is highly desirable.

Software Engineer Job Overview: We are seeking a Python Senior Software Engineers to build and ... Experience with AI/ML, OCR, and cloud platforms (especially Azure) is highly desirable.

Software Engineer Job Overview: We are seeking a Python Senior Software Engineers to build and ... Experience with AI/ML, OCR, and cloud platforms (especially Azure) is highly desirable.

We are looking to hire numerous Engineers; Priority will go to those with Steel/Metals software ... ML/AI and advanced optimization technologies Benefits: • Dental insurance • Disability ...

Data & Software Engineer

Chicago, IL

$118K - $141K/yr

Experience with AI/ML frameworks or APIs (e.g., OpenAI,HuggingFace,LangChain, or similar ... For our Data & Software Engineer positions, our compensation ranges from$75,000 to $93,000, which ...

We are looking to hire numerous Engineers; Priority will go to those with Steel/Metals software ... expand into ML/AI and advanced optimization technologies Benefits: · Dental insurance · ...

We are looking to hire numerous Engineers; Priority will go to those with Steel/Metals software ... expand into ML/AI and advanced optimization technologies Benefits: · Dental insurance · ...

Senior Software Engineer

Chicago, IL · On-site

$102K - $179K/yr

You will partner closely with AI/ML engineers, data scientists, and cross-functional teams to ... Evaluate emerging AI engineering trends, AI-assisted development tools, and modern software ...

Senior Software Engineer

Chicago, IL · On-site

$102K - $179K/yr

You will partner closely with AI/ML engineers, data scientists, and cross-functional teams to ... Evaluate emerging AI engineering trends, AI-assisted development tools, and modern software ...

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Showing results 1-20

Software Engineer Ml information

See Chicago, IL salary details

$65.4K

$152K

$211.7K

How much do software engineer ml jobs pay per year?

As of Sep 1, 2026, the average yearly pay for software engineer ml in Chicago, IL is $151,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $123,600.00 and $178,200.00 per year, depending on experience, location, and employer.

What does a software engineer ML do?

A Software Engineer, ML (Machine Learning) designs, develops, and deploys software systems that use machine learning algorithms to solve complex problems. They work on tasks such as building data pipelines, training and testing machine learning models, and integrating these models into production applications. They collaborate closely with data scientists, product managers, and other engineers to ensure that ML systems are scalable, efficient, and meet business objectives. Their work often involves programming, data analysis, and staying up-to-date with the latest developments in AI and machine learning.

What are the key skills and qualifications needed to thrive as a software engineer ML?

To thrive as a Software Engineer ML, you need strong proficiency in programming (especially Python), algorithms, machine learning theory, and a relevant degree in computer science or a related field. Experience with ML frameworks like TensorFlow or PyTorch, and familiarity with cloud computing platforms and version control systems are typically required. Analytical thinking, problem-solving, and effective communication skills help you stand out in collaborative and complex project environments. These skills are vital to efficiently develop, deploy, and maintain robust machine learning solutions that drive business value.

What are some common challenges faced by software engineers working in machine learning, and how can they be addressed?

Software Engineers in Machine Learning often encounter challenges such as managing large datasets, ensuring model accuracy, and keeping up with rapidly evolving frameworks and tools. Collaboration with data scientists and domain experts is essential to align technical solutions with business goals. Staying current through continuous learning and leveraging cloud-based platforms or MLOps practices can help streamline workflows and improve model deployment. Additionally, effective communication within cross-functional teams is crucial for addressing both technical and non-technical challenges.

What job categories do people searching Software Engineer Ml jobs in Chicago, IL look for?

The top searched job categories for Software Engineer Ml jobs in Chicago, IL are:

Infographic showing various Software Engineer Ml job openings in Chicago, IL as of August 2026, with employment types broken down into 87% Full Time, 10% Part Time, and 3% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $151,971 per year, or $73.1 per hour.

Senior Research Engineer - ML Systems

Permute AI, Inc

Chicago, IL • On-site

$150K - $250K/yr

Full-time

Posted 5 days ago


Job description

Senior Research Engineer - ML Systems
Employment Type: Full-time
Company: Permute (www.permute.ai)
Overview
Permute is seeking a Senior Research Engineer to productionize, optimize, and extend the model systems that power AI reasoning over structured data. This role is for builders who can move from research ideas to reliable production systems, including the profiling, testing, and failure handling that prototypes often skip.
We care as much about how you think and build as we do about your background. The ideal candidate can implement research, diagnose model and systems performance, write clean production code, and make sound architectural decisions in a fast-moving startup environment.
Responsibilities
  • Productionize and optimize our existing learned evidence architecture for structured data
  • Improve training and inference performance, including throughput, latency, memory use, reliability, and cost
  • Port and optimize model training and inference workloads from CPU to GPU
  • Build production systems supporting model training, evaluation, deployment, and inference
  • Develop tooling for experimentation, reproducibility, monitoring, and observability
  • Write clean, maintainable Python and PyTorch systems that integrate with Permute's broader platform
  • Design and evaluate new heads, layers, objectives, and fine-tuning methods
  • Explore new model variants, including transformer-based architectures and reinforcement learning
  • Collaborate with engineering and product teams to deliver model capabilities that power production AI features
Required Qualifications
  • Strong background in machine learning research and ML systems
  • Experience building and training models with PyTorch
  • Strong foundation in algorithms, statistics, optimization, and experimental design
  • Strong software engineering and system architecture skills
  • 5+ years building ML or performance-sensitive software systems

Preferred Background
  • Degree in Mathematics, Physics, Computer Science, or a related technical field

Experience with:
  • End-to-end production ML systems
  • Model training, MLOps, evaluation, and deployment
  • Performance engineering, including CUDA, Triton, quantization, or model compilation
  • Transformers, fine-tuning, post-training, or reinforcement learning
  • Meaningful contributions to open-source ML frameworks or model implementations