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

Chime Financial, Inc

Senior AI/ML Engineer

Chicago, IL · On-site

$107K - $147K/yr

About the role We're hiring for a Senior AI/ML Engineer, Growth & Marketing AI to help us build the ... Develop and deploy sequential deep learning models and traditional machine learning systems to ...

J.P. Morgan

Applied AI/ML - Vice President

Chicago, IL · On-site

Work with Product Owners and Software Engineers to productionize the models and Partners closely ... Extensive experience with Machine Learning and Deep Learning toolkits (e.g.: Transformers, Hugging ...

Cna

Senior Data AI Engineer

Chicago, IL · On-site

$109K - $148K/yr

Productionize and operationalize AI solutions and advanced analytics in a DevOps/MLOpsenvironment ... Demonstrated experience with machine learning, deep learning, information retrieval, NLP, or data ...

Referrals Only

Lead Machine Learning Engineer

Chicago, IL

$105K - $139K/yr

Lead Machine Learning Engineers at Thoughtworks use modern architectures to develop end-to-end ... You will leverage your deep understanding of modern architectures to lead the development of ...

PayPal

Sr Machine Learning Engineer

Chicago, IL · On-site

$57.50 - $76/hr

... deep learning architectures (e.g., CNNs, RNNs). * Proficiency in programming and big-data technologies, with hands-on experience in tools such as Python (Scikit-learn, TensorFlow), SQL, Hadoop, and ...

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Deep Learning Developer information

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How much do deep learning developer jobs pay per hour?

As of Jul 20, 2026, the average hourly pay for deep learning developer in Chicago, IL is $39.60, according to ZipRecruiter salary data. Most workers in this role earn between $33.65 and $44.09 per hour, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior Deep Learning Developer or AI research lead, often involving advanced skills in machine learning frameworks, data modeling, and programming. Such roles usually require extensive experience, specialized knowledge, and may include responsibilities like developing innovative AI solutions or leading AI teams in tech companies or research institutions.

What are the key skills and qualifications needed to thrive as a Deep Learning Developer, and why are they important?

To thrive as a Deep Learning Developer, you need a strong background in computer science, mathematics, and proficiency in programming languages like Python, often supported by a degree in a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms or GPU acceleration, are commonly required technical skills. Analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this role. These competencies are crucial for designing, training, and deploying advanced neural network models that address complex real-world problems.

What are Deep Learning Developers?

Deep Learning Developers are specialized software engineers or data scientists who design, build, and implement artificial intelligence systems using deep learning techniques. They work with neural networks, large datasets, and various frameworks like TensorFlow or PyTorch to develop models for tasks such as image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, optimization, and deployment to solve complex problems that require advanced pattern recognition. Deep Learning Developers often collaborate with AI researchers, data engineers, and product teams to integrate intelligent features into applications.

Which 3 jobs will survive AI?

Deep Learning Developers are likely to continue to be in demand as AI advances because they design and improve AI models, requiring specialized skills in programming, mathematics, and data analysis. Other roles expected to persist include AI ethics specialists and AI system trainers, as human oversight and ethical considerations remain essential. These jobs involve complex problem-solving and domain expertise that are difficult to fully automate.

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

AspectDeep Learning DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with neural networksBachelor's or Master's in CS, Data Science, or related; knowledge of algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural networksData-driven companies, software firms, industries applying machine learning
Industry UsagePrimarily in AI research, neural network development, deep learning projectsBroader application including predictive modeling, data analysis, and ML systems

Deep Learning Developers specialize in neural networks and deep learning models, often working on AI research and complex algorithms. Machine Learning Engineers have a broader focus on developing, deploying, and maintaining machine learning models across various applications. While both roles require similar educational backgrounds, their focus areas and industry applications differ.

What are some common challenges Deep Learning Developers face when deploying models to production environments?

Deep Learning Developers often encounter challenges such as optimizing model performance for real-time inference, managing resource constraints (like GPU/CPU availability), and ensuring model reproducibility across different environments. Additionally, integrating deep learning models into existing software systems and maintaining them over time can be complex, especially as data and requirements evolve. Collaborating closely with DevOps, data engineers, and QA teams is essential to address these challenges and ensure smooth deployment and ongoing reliability.

What engineer makes $500,000 a year?

Highly experienced deep learning developers or AI engineers with specialized skills in neural networks, large-scale data processing, and advanced machine learning frameworks can earn $500,000 or more annually, especially in senior or leadership roles at major tech companies or startups. Such roles often require advanced degrees, extensive experience, and a strong track record of deploying impactful AI solutions.

What engineers make $300,000 a year?

Deep learning developers and AI engineers with extensive experience, advanced skills in machine learning frameworks, and strong domain expertise can earn $300,000 or more annually, especially in high-demand industries or senior roles. Compensation often includes base salary, bonuses, and stock options, particularly at leading tech companies or startups with significant funding.
Deep Learning Developer jobs near you
AI Developer (Contract to Hire)

AI Developer (Contract to Hire)

DivIHN Integration Inc

Deerfield, IL • On-site

Contractor

Re-posted 20 days ago

Job description

For further inquiries regarding the following opportunity, please contact our Talent Specialist
Lavanya at 224 369 0873 
 
Title: AI Developer - Contract to Hire
Location: Deerfield, IL
Duration: 12 Months with possibility of extension
 
Preferred CST Time Zone
 
Job Description
Essential Duties and Responsibilities:
  • Work with technical and business teams to develop GenAI solutions for scenarios like
    • Text Extraction
    • Speech to Text
    • Chat Assistant with Knowledge Base
    • Chat Assistant with Transactional Data
    • Workflow Automation using AI Agents
  • Apply your knowledge of Gen AI frameworks and deployment architectures to build solutions and recommend best practices.
  • Evaluate options, develop Proof of concepts, and review code and solutions from other team members.
  • Understanding of full-stack architecture is a strong plus.
 
Qualifications
  • 5+ years of design, implementation, or consulting in applications and infrastructures experience
  • Strong familiarity with AWS cloud services.
  • 3+ years of experience in various phases of Machine Learning, Artificial Intelligence and Deep Learning solutions using AWS technologies.
  • Experience in implementing AI/Generative AI solutions using AWS Sagemaker, AWS Bedrock and other AI services like AWS Transcribe, AWS Textract, AWS Kendra, AWS Translate and AWS Rekognition, etc.
  • Demonstrated understanding of prompt engineering and application of it to mentioned use cases.
  • Evaluate LLM outputs for hallucination, toxicity, bias, and factual correctness.
  • Implement context caching and memory management patterns to implement well performing applications.
  • Coding experience in implementing solutions using various AWS Services.
  • Proficiency in programming languages such as Python and NodeJS preferred.
  • Proficiency in creating and using REST APIs.
  • Build and deploy AI/GenAI solutions on AWS
  • Develop and manage end-to-end data/AI pipelines
  • Create chat assistants and integrate APIs
  • Write production-ready Python code
  • Innovate and automate digital processes
  • Own projects from design to deployment
  • No specific Degree mentioned, Bachelors preferred.
  • Strong in Python (Node.js is a plus), 3+ years in AI