ZipRecruiter

Log In

2

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

Career Renew

Senior Machine Learning Engineer

Chicago, IL · Remote

$165K - $225K/yr

... remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ... The ideal candidate will have deep expertise in Machine Learning and building generalizable ...

BMO Capital Markets

Senior Data Scientist

Chicago, IL · On-site +1

$122K - $228K/yr

Data Analytics & Reporting This is ideally a hybrid role but open to remote Role Overview We are ... Apply advanced analytics, machine learning, deep learning, and AI methodologies to build predictive ...

Huntington

Lead Data Scientist

Chicago, IL · On-site +1

$83K - $170K/yr

Determines requirements that will be used to train and evolve deep learning models and algorithms ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

UnitedHealth Group

Lead AI/ML Engineer - Remote

Schaumburg, IL · On-site +1

$100K - $132K/yr

Apply advanced knowledge of machine learning, deep learning, statistics, and experimental methodologies to build high-quality, data-driven solutions * Partner closely with product, business, and ...

UnitedHealth Group

Lead AI/ML Engineer - Remote

Schaumburg, IL · On-site +1

$100K - $132K/yr

Apply advanced knowledge of machine learning, deep learning, statistics, and experimental methodologies to build high-quality, data-driven solutions * Partner closely with product, business, and ...

ONETRACK.AI

Sales - Build Your Own Role

Chicago, IL · On-site +1

Founded in 2017, OneTrack combines computer vision, deep learning, and low-cost edge sensors to ... PTO and Flexible working hours and remote work options * Opportunities for professional growth and ...

Numerator

Technical Product Manager

Chicago, IL · Remote

$88K - $121K/yr

This role will work with many other back-end development teams, including Deep Learning and Mobile ... Work effectively with remote teams across multiple time zones, domestic and off-shore * Leverage ...

Numerator

Technical Product Manager

Chicago, IL · Remote

$88K - $121K/yr

This role will work with many other back-end development teams, including Deep Learning and Mobile ... Work effectively with remote teams across multiple time zones, domestic and off-shore * Leverage ...

Addison Group

Sr. Data Scientist

Chicago, IL · On-site +1

$85 - $100/hr

Remote Contract Pay: $85/hr - $100/hr The Senior Data Scientist will design and implement AI ... and deep learning methods. • Expertise in feature engineering, model evaluation, and ...

Addison Group

Sr. Data Scientist

Chicago, IL · Remote

$85 - $100/hr

Remote Contract Pay: $85/hr - $100/hr The Senior Data Scientist will design and implement AI ... and deep learning methods. • Expertise in feature engineering, model evaluation, and ...

Adidev Technologies Inc

AI/ML

Chicago, IL · Remote

Hands-on experience with Deep Learning, LLM, Python, TensorFlow, PyTorch and other AI frameworks ... Support, even from afar, with our remote assistance. Regular salary reviews? You betcha! Ready to ...

Adidev Technologies

AI/ML

Des Plaines, IL · Remote

Hands-on experience with Deep Learning, LLM, Python, TensorFlow, PyTorch and other AI frameworks ... Support, even from afar, with our remote assistance. * Regular salary reviews? You betcha! Ready to ...

next page

Showing results 1-20

All JobsDeep Learning JobsRemote Deep Learning JobsRemote Deep Learning Jobs in Chicago, IL

Remote Deep Learning information

See Chicago, IL salary details

$11.3K

$86.4K

$144.2K

How much do remote deep learning jobs pay per year?

As of Jul 14, 2026, the average yearly pay for remote deep learning 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 a Remote Deep Learning job?

A Remote Deep Learning job involves working with artificial intelligence and machine learning models, particularly using deep neural networks, from a location outside a traditional office, often from home. Professionals in this field design, build, and optimize algorithms that enable computers to learn from large amounts of data. They often work on projects such as image and speech recognition, natural language processing, or autonomous systems. The remote aspect allows flexibility and access to global opportunities, but requires strong communication skills and the ability to collaborate virtually with teams.

What are some common challenges faced by remote deep learning engineers, and how can they be addressed?

Remote deep learning engineers often encounter challenges such as limited access to high-performance computing resources, communication barriers with distributed teams, and difficulties in collaborating on large codebases or datasets. These issues can be mitigated by leveraging cloud-based platforms for scalable computing, using clear communication tools like Slack or Zoom for regular check-ins, and employing version control systems like Git for collaborative code management. Proactively setting up workflows and documentation helps ensure smooth collaboration and project continuity within a remote environment.

How can I make $100,000 a year working from home?

A remote deep learning professional can reach a $100,000 annual income by gaining advanced skills in machine learning frameworks, building a strong portfolio, and working for companies that offer competitive salaries or freelance projects. Earning this level often requires experience, specialized knowledge, and the ability to deliver high-quality models efficiently. Certifications in deep learning and proficiency with tools like Python, TensorFlow, or PyTorch can also enhance earning potential.

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 machine learning engineer, AI research director, or chief AI officer, often requiring advanced skills in deep learning, data science, and programming. These roles usually involve leadership responsibilities, extensive experience, and may include stock options or bonuses as part of compensation packages.

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

AspectRemote Deep LearningRemote Machine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with neural networksBachelor's/Master's in CS, Data Science, or related; experience with algorithms and data modeling
Work EnvironmentCollaborative teams, research-focused, often in tech or AI companiesDevelopment teams, data-driven projects, across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsTech companies, finance, healthcare, e-commerce

Remote Deep Learning specialists focus on designing and training neural networks for AI applications, often requiring advanced knowledge of deep neural architectures. Remote Machine Learning Engineers work on developing algorithms and models for broader data analysis and predictive tasks. While both roles involve machine learning, deep learning emphasizes neural networks, whereas machine learning engineers may work with a variety of algorithms across industries.

Which 3 jobs will survive AI?

In the field of remote deep learning, roles such as data scientists, machine learning engineers, and AI research scientists are likely to persist due to their reliance on complex problem-solving, domain expertise, and ongoing innovation. These jobs require advanced skills in programming, mathematics, and understanding of AI frameworks, making them less susceptible to automation by AI systems. Continuous learning and staying updated with new tools and techniques are essential for long-term career stability in this area.

How to make $1000 a week remotely?

Remote deep learning professionals can earn $1000 or more weekly by taking on freelance projects, consulting, or working for companies that pay competitive rates. Building a strong portfolio, acquiring relevant skills in Python and machine learning frameworks, and obtaining certifications can help increase earning potential. Consistent work and specialized expertise are key to reaching this income level remotely.

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

To thrive as a Remote Deep Learning Engineer, you need strong programming skills in Python, a deep understanding of machine learning algorithms, and typically a degree in computer science, engineering, or a related field. Proficiency with frameworks like TensorFlow or PyTorch, as well as cloud computing platforms such as AWS or Google Cloud, is essential, and certifications in these technologies can be advantageous. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for remote collaboration and project delivery. These skills ensure effective development, deployment, and maintenance of deep learning models while working independently in distributed teams.
What are the most commonly searched types of Deep Learning jobs in Chicago, IL? The most popular types of Deep Learning jobs in Chicago, IL are:
What are popular job titles related to Remote Deep Learning jobs in Chicago, IL? For Remote Deep Learning jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Remote Deep Learning jobs in Chicago, IL look for? The top searched job categories for Remote Deep Learning jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Remote Deep Learning jobs? Cities near Chicago, IL with the most Remote Deep Learning job openings:
Remote Deep Learning jobs near you

Senior Machine Learning Engineer

Career Renew

Chicago, IL • Remote

$165K - $225K/yr

Full-time

Posted 21 days ago

Job description

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus equity.
We are the leading virtual staining company revolutionizing digital pathology adoption worldwide through cutting-edge AI-powered technology. Our solutions deliver diagnostic-quality results in minutes while preserving tissue samples for comprehensive analysis.
Our breakthrough DeepStain™ and ReStain™ technologies enable unlimited virtual staining from a single tissue sample, eliminating the bottlenecks and limitations of traditional chemical staining processes. This innovation supports the critical evolution from research applications to clinical deployment, empowering laboratories to advance their digital pathology capabilities while reducing chemical waste, improving operational efficiency, and expanding diagnostic possibilities.

About the Role

We are seeking an experienced Senior ML Engineer to join our team who owns the representation-learning and generative modeling stack that powers Pictor’s virtual staining. The ideal candidate will have deep expertise in Machine Learning and building generalizable, production-ready models, and evaluations that stand up in clinical workflows.
Design and implement novel computer vision and deep learning algorithms for virtual staining and digital pathology applications
Conduct rigorous experiments to evaluate algorithm performance, validate research hypotheses, and drive iterative improvements
Develop and advance ML models leveraging Vision Transformers, Diffusion Models, GANs, and generative architectures for image-to-image translation tasks
Apply classical and learned image enhancement, denoising, and semantic segmentation techniques to histopathology imaging challenges
Explore image representation in latent space for efficient, high-fidelity virtual staining
Stay current with state-of-the-art research, identifying opportunities to apply novel techniques to PictorLabs’ product roadmap

Collaboration
Collaborate with ML Engineering and software teams to translate research prototypes into production-ready systems meeting latency and throughput requirements
Work with large-scale pathology datasets to train, validate, and fine-tune foundation models and custom architectures
Partner with software engineers, data scientists, and pathology domain experts to integrate research into production systems
Contribute to best practices for data engineering, data governance, and data quality across research and production pipelines
Leverage AI coding and ideation tools to accelerate research velocity and prototype new approaches

Required Qualifications

PhD (preferred) or Master’s degree in Computer Science, Electrical Engineering, or a related field
Deep expertise in computer vision and deep learning, with hands-on experience in one or more of: Vision Transformers, Diffusion Models, GANs, semantic segmentation, or classical image enhancement and denoising
Expert proficiency in Python and PyTorch and other scientific computing environments a plus
Strong mathematical foundation in linear algebra, probability, and optimization
Experience with large-scale model training, distributed computing, or cloud ML infrastructure (AWS, GCP, or Azure)
Knowledge of handling large scale image data, data version controls, model registry, has experience dealing with ML lifecycles
Experience with feature search, data balancing, and data curation pipelines.
Knowledge of software engineering best practices including version control (Git) and CI/CD pipelines
Excellent collaboration and communication skills, with the ability to work effectively in a fast-paced, cross-functional international startup environment
Extensive use of AI tools for coding, optimization, and ideation

Preferred Qualifications

Experience with medical imaging, digital pathology, or whole slide image (WSI) processing
Experience with LoRAs, transformer architecture and state of the art image to image translation models (Flux 2, Z-Image) and the Hugging face ecosystem
Background in generative models and fine-tuning of foundation models
Experience with GPU acceleration and optimization, including CUDA kernel engineering, TensorRT/ONNX export, and inference serving frameworks such as Triton
Experience with hosting computer vision model inference on NVIDIA DGX Spark.
Understanding of FDA regulatory requirements for AI/ML in medical devices
Experience with MLOps tools (MLflow, Kubeflow) and model versioning practices
Develop tools and frameworks to streamline ML research workflows, experimentation, and reproducibility

What We Offer

The opportunity to work on technology that directly improves patient outcomes and transforms clinical diagnostics, alongside a talented team of engineers and researchers pushing the boundaries of AI in healthcare. You will have the freedom to pursue high-impact research while seeing your work deployed at scale in real clinical environments.