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Deep Learning Ai Jobs in Chicago, IL (NOW HIRING)

NAVA Software Solutions

Sr. AI/ML Engineer

Deerfield, IL · On-site

$106K - $145K/yr

Chicago IL -Hybrid - 3 days/week onsite Duration: 6-12 months Required: * 7+ years of hands-on experience in applied machine learning, deep learning, and AI system deployment * Strong Python ...

Lightspeed

AI & Machine Learning Engineer

Northbrook, IL · On-site

$100 - $130/hr

Develop deep learning pipelines for object detection, segmentation, and pose estimation * Build ... AI/ML Expertise * 4+ years hands‑on ML engineering building and deploying production models

J.P. Morgan

Applied AI/ML Senior Associate

Chicago, IL · On-site

$60K - $61K/yr

As a Senior Associate Applied AI/ML Scientist within our payment solutions team, you will be ... Proficient in Python with hands-on experience in Machine learning and Deep learning frameworks (e.g ...

Varsity Tutors

Machine Learning Tutor

Naperville, IL · Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ...

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All JobsDeep Learning Ai JobsDeep Learning Ai Jobs in Chicago, IL

Deep Learning Ai information

See Chicago, IL salary details

$11.3K

$86.4K

$144.2K

How much do deep learning ai jobs pay per year?

As of Aug 16, 2026, the average yearly pay for deep learning ai in Chicago, IL is $86,414.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,200.00 and $143,200.00 per year, depending on experience, location, and employer.

What is the difference between Deep Learning Ai vs Machine Learning Engineer?

AspectDeep Learning AiMachine Learning Engineer
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of neural networksDegree in Computer Science, Data Science, or related fields; programming skills in Python, R
Work EnvironmentResearch labs, AI development teams, tech companies focusing on AI modelsSoftware development teams, data analysis projects across various industries
Industry UsagePrimarily in AI research, autonomous systems, NLP, computer visionAcross industries for predictive modeling, data analysis, automation

Deep Learning Ai specialists focus on designing and implementing neural network models for complex AI tasks, often requiring advanced knowledge of deep neural networks. Machine Learning Engineers develop broader machine learning models, including traditional algorithms. While both roles require similar educational backgrounds, Deep Learning Ai roles are more specialized in neural networks and AI research, whereas Machine Learning Engineers work across a wider range of algorithms and applications.

What are some common challenges faced by professionals working in deep learning AI, and how can they be addressed?

Professionals in Deep Learning AI often encounter challenges such as managing large datasets, ensuring model accuracy, and addressing issues like overfitting. Collaboration with data engineers and domain experts is crucial to ensure high-quality data and relevant feature selection. Additionally, staying up-to-date with rapidly evolving frameworks and algorithms requires continuous learning and participation in knowledge-sharing within the team. Regular code reviews and experimentation with different architectures can help overcome technical obstacles and improve model performance.

What are the key skills and qualifications needed to thrive as a deep learning AI engineer?

To thrive as a Deep Learning AI Engineer, you need a strong background in mathematics, programming (especially Python), and experience with neural networks, typically supported by a degree in computer science, engineering, or a related field. Proficiency with deep learning frameworks such as TensorFlow or PyTorch, and knowledge of tools like CUDA for GPU acceleration, are essential; relevant certifications can be advantageous. Analytical thinking, creativity, and effective communication are important soft skills for solving complex problems and collaborating with cross-functional teams. These skills and qualities are crucial for building robust AI models and driving innovation in this rapidly evolving field.

What is a deep learning AI professional?

Deep Learning AI professionals are experts who design, develop, and implement artificial intelligence systems that use deep neural networks to analyze complex data and solve tasks such as image recognition, natural language processing, and autonomous decision-making. They work with large datasets and advanced algorithms to build models that can learn and improve over time. These professionals often have a background in computer science, mathematics, or engineering, and are skilled in programming languages like Python and frameworks such as TensorFlow or PyTorch.

What are popular job titles related to Deep Learning Ai jobs in Chicago, IL?

For Deep Learning Ai jobs in Chicago, IL, the most frequently searched job titles are:

What job categories do people searching Deep Learning Ai jobs in Chicago, IL look for?

The top searched job categories for Deep Learning Ai jobs in Chicago, IL are:

What cities near Chicago, IL are hiring for Deep Learning Ai jobs?

Cities near Chicago, IL with the most Deep Learning Ai job openings:

Deep Learning Ai jobs near you
Infographic showing various Deep Learning Ai job openings in Chicago, IL as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $86,414 per year, or $41.5 per hour.

Campus AI Research Engineer - Deep Learning (Intern)

Jump Trading

Chicago, IL • On-site

$300K/yr

Other

Re-posted 8 days ago

Job description

Campus Ai Research Engineer - Deep Learning (Intern)

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.

We are seeking research scientists with a demonstrated ability to apply machine learning to achieve state-of-the-art capabilities in complex and challenging domains. The ideal person for this role will be capable of implementing an open-ended research project from concept to production and continuously improving model design, tools, and infrastructure. Potential projects may target any area of the quantitative research and monetization process. We believe that successful research efforts require a fluid mix of skills including AI/ML expertise, engineering pragmatism, statistics, and market intuition.

What You'll Do:

  • Apply state-of-the-art techniques to complex and challenging domains.
  • Work closely with researchers and quants to build flexible and reusable frameworks for financial ML.
  • Optimize training pipelines to make the best use of our HPC resources.
  • Integrate ML models into production systems where latency matters.
  • Work across a mix of programming languages: C / C++ / Python / CUDA and other low-level GPU languages.
  • Build large-scale ML systems that are observable, performant, and flexible. Help improve productivity by reducing the iteration cycle time on research.
  • Other duties as assigned or needed.

Skills You'll Need:

  • Strong publication record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent and/or contributions to open-source AI research
  • Strong general ML background with exposure to modern deep learning techniques and/or language modeling architectures (e.g. transformers, SSMs)
  • Solid development skills in Python and/or C++
  • Familiarity with ML libraries/frameworks such as PyTorch, JAX, and/or TensorFlow
  • Intellectual curiosity, versatility, and originality combined with a pragmatic outlook
  • Ability to thrive in a collaborative, team-oriented environment
  • Ability to reason through quantitative problems and communicate effectively with trading researchers
  • Reliable and predictable availability

Bonus Points:

  • Experience with HPC and distributed large model training
  • Experience with GPU performance optimization (CUDA or ROCm)
  • Experience with end-to-end model development
  • Strong opinions on best practices in ML research, tooling, and/or infrastructure

INTERNATIONAL STUDENTS are encouraged to apply. We accept students eligible for CPT/OPT and we sponsor work visas for full-time positions.

The estimated base salary for this role (annualized) is $300,000 per year.

Apply