AI Image Segmentation Engineer – Chicago, IL

Are you a skilled engineer passionate about pushing the boundaries of computer vision and artificial intelligence? We are seeking an AI Image Segmentation Engineer to join a forward-thinking tech company based in Chicago, IL. In this role, you will lead the development of cutting-edge image segmentation models that power real-world applications in healthcare, autonomous systems, retail, and beyond. If you thrive at the intersection of deep learning and innovation, this is your opportunity to shape the next generation of intelligent imaging solutions.

Drive Impactful AI Solutions in the Heart of Chicago

A leading AI-driven technology firm in Chicago, IL is hiring an AI Image Segmentation Engineer to enhance its advanced computer vision capabilities. The ideal candidate will have hands-on experience in building and deploying image segmentation models using state-of-the-art neural networks. You’ll collaborate with cross-functional teams to turn complex visual data into actionable insights. If you’re passionate about precision, performance, and building scalable AI systems, we invite you to bring your expertise to a team that values innovation and real-world impact.

Key Responsibilities of the AI Image Segmentation Engineer – Chicago, IL

Advanced Model Development: Design, develop, and optimize state-of-the-art image segmentation algorithms using deep learning frameworks such as TensorFlow, PyTorch, or similar. Leverage convolutional neural networks (CNNs), transformers, and other architectures to deliver precise and efficient segmentation solutions.

Data Pipeline & Preprocessing: Build and maintain scalable data pipelines for image ingestion, preprocessing, augmentation, and annotation. Ensure the quality, consistency, and usability of large-scale image datasets for training and validation.

Model Training & Evaluation: Train segmentation models using supervised, semi-supervised, or unsupervised techniques. Evaluate performance using relevant metrics (e.g., IoU, Dice score), fine-tune hyperparameters, and implement techniques to reduce overfitting and improve generalization.

Real-World Deployment: Integrate models into production environments and optimize them for real-time inference. Collaborate with backend and frontend teams to ensure seamless model deployment, API integration, and scalability across platforms.

Cross-Functional Collaboration: Work closely with product managers, UX designers, and fellow AI researchers to translate business goals into technical solutions. Contribute to project planning, timeline estimation, and delivery of milestones.

Research & Innovation: Stay current with advancements in computer vision, deep learning, and AI. Experiment with novel segmentation techniques and publish findings or contribute to internal knowledge-sharing initiatives.

Performance Optimization: Continuously monitor and improve the performance, accuracy, and speed of segmentation models. Utilize hardware acceleration (e.g., GPUs, TPUs) and model compression techniques when necessary.

Quality Assurance & Testing: Establish rigorous testing frameworks to validate model robustness and performance across different environments, edge cases, and image types.

Documentation & Reporting: Maintain thorough documentation of model architectures, training procedures, and performance benchmarks. Communicate progress, insights, and risks effectively to stakeholders and technical leadership.

Ethics & Compliance: Ensure AI models meet ethical guidelines, avoid bias, and adhere to data privacy standards. Follow best practices in responsible AI development and deployment.

What the Client is Looking for in You

As the AI Image Segmentation Engineer – Chicago, IL, the client is seeking a highly skilled and innovative professional with a strong foundation in computer vision and deep learning. You should be a results-driven engineer with a passion for solving complex imaging challenges and deploying AI-powered solutions at scale.

Proven Expertise in Image Segmentation and Deep Learning

The client is looking for a candidate with hands-on experience in designing and training image segmentation models using leading deep learning frameworks such as TensorFlow, PyTorch, or Keras. A proven track record of working with architectures like U-Net, Mask R-CNN, or transformers for segmentation tasks is highly valued. Experience applying these models in real-world domains such as medical imaging, autonomous systems, or retail is a strong plus.

Strong Theoretical Knowledge and Practical Implementation

You should possess a deep understanding of computer vision principles, neural network architectures, and data preprocessing techniques. The ability to translate academic research into production-ready models, along with experience in optimization, evaluation, and tuning, is critical to success in this role.

Experience in Scalable Model Deployment

The client is seeking an engineer who has deployed AI models into production environments and is comfortable with building robust, scalable pipelines. Experience with containerization tools (Docker, Kubernetes), cloud platforms (AWS, GCP, Azure), and API integrations will be highly regarded.

Collaborative Mindset and Cross-Functional Communication

This role requires close collaboration with research scientists, data engineers, and product teams. The ideal candidate will be an effective communicator who can clearly present technical concepts to both technical and non-technical stakeholders and contribute to a shared vision.

Innovation-Driven and Research-Oriented

The client values professionals who are always learning and staying up to date with the latest advancements in AI. Participation in research, publications, conferences, or contributing to open-source projects is a plus. You should demonstrate curiosity, creativity, and a strong drive to push technological boundaries.

Analytical Thinking and Performance Focus

Strong analytical and problem-solving skills are essential. The client is looking for someone who can optimize model performance, troubleshoot bottlenecks, and deliver measurable results. Attention to detail and a data-driven approach to development and testing are key attributes for this role.

Commitment to Ethical AI and Quality Standards

You must adhere to responsible AI development practices and demonstrate a commitment to data privacy, fairness, and regulatory compliance. Ensuring the ethical deployment of AI models and maintaining high standards of quality assurance are critical expectations.

FAQs About the Role – AI Image Segmentation Engineer – Chicago, IL

What are the key responsibilities of the AI Image Segmentation Engineer?
As an AI Image Segmentation Engineer, your primary responsibilities include designing, training, and deploying advanced image segmentation models using deep learning techniques. You will preprocess datasets, build scalable ML pipelines, collaborate with cross-functional teams, and ensure the performance and accuracy of models in real-world applications. Additionally, you’ll be expected to stay updated with the latest research in computer vision and contribute to continuous innovation within the team.
What qualifications and experience are required for this position?
The ideal candidate should have a degree in Computer Science, Engineering, or a related field, with a strong background in computer vision and deep learning. Experience with image segmentation models such as U-Net, Mask R-CNN, or DeepLab, and proficiency in frameworks like TensorFlow or PyTorch are essential. Familiarity with deploying models in production environments and working with large-scale image datasets is highly desirable. A master’s degree or Ph.D. in a relevant field is a plus.
What technical skills are critical for success in this role?
Key technical skills include strong programming abilities in Python, expertise in neural network design and evaluation, and proficiency with tools such as OpenCV, NumPy, and Scikit-learn. Experience with cloud platforms (AWS, GCP, or Azure), containerization (Docker/Kubernetes), and CI/CD pipelines for model deployment is also important. Knowledge of data annotation tools and experience working with real-time inference systems can be beneficial.
What challenges can I expect in this role?
You can expect challenges such as optimizing model accuracy on noisy or unstructured image data, reducing inference latency for real-time applications, and deploying models at scale in production environments. You’ll also need to address edge cases and generalize models across diverse domains while maintaining high performance and compliance with ethical AI standards.
What kind of impact will I have in this role?
Your work will directly contribute to developing cutting-edge AI solutions with real-world applications in fields such as healthcare, autonomous systems, manufacturing, or e-commerce. By improving the accuracy and efficiency of image segmentation models, you’ll help drive product innovation, enhance user experiences, and support business growth through AI-powered insights.
What is the work environment and company culture like?
The company offers a collaborative and innovation-driven environment where engineers are encouraged to experiment, take ownership of their projects, and stay at the forefront of AI research. The team values knowledge sharing, creativity, and continuous learning. You’ll be part of a supportive culture that embraces agility, diversity, and technical excellence.

What Remuneration Can You Expect from This Job?

As an AI Image Segmentation Engineer in Chicago, IL, you can expect a competitive and comprehensive compensation package that reflects your specialized skills in computer vision and machine learning. The remuneration for this role typically includes the following components:

1. Base Salary

The annual base salary for AI engineers with expertise in image segmentation typically ranges between $120,000 and $180,000, depending on experience, education, and the complexity of the role. Senior professionals or those with Ph.D.-level experience may command salaries beyond this range.

2. Performance-Based Bonuses

You may be eligible for annual bonuses tied to project success, model performance in production, or company milestones. These bonuses usually range from 10% to 25% of your base salary and reward technical excellence, innovation, and collaboration.

3. Equity and Stock Options

If the company is a startup or a growth-stage tech firm, equity in the form of stock options or RSUs (Restricted Stock Units) may be offered. These equity incentives give you a stake in the company’s long-term success and can significantly boost your total compensation.

4. Comprehensive Benefits

Expect a full suite of employee benefits, including:

Health, dental, and vision insurance
401(k) retirement plan with employer matching
Paid time off (PTO), sick leave, and holidays
Continuing education support or learning stipends
Mental health and wellness programs

5. Relocation Support and Signing Bonus

If you’re relocating to Chicago or being hired from a competitive role, you may be offered a signing bonus or relocation package, typically ranging from $5,000 to $20,000, depending on company policy and your seniority.

6. Career Growth Incentives

Companies may also offer additional perks like:

Annual tech conference passes
Access to in-house research funding
Publications and patents support
Opportunities to lead or mentor junior AI talent

Total Compensation Potential

Including base salary, bonuses, equity, and benefits, your total annual compensation package could range from $140,000 to over $250,000, especially in high-impact or leadership-level engineering roles.

How to Apply

If you are an innovative and skilled professional with a deep understanding of AI image segmentation and machine learning, we encourage you to apply for the AI Image Segmentation Engineer position in Chicago, IL. This is an exciting opportunity to contribute to cutting-edge projects and make an impact on the company’s AI-driven initiatives.

To apply, please submit the following:

Resume: Include details of your relevant experience in AI, deep learning, and computer vision, with a focus on image segmentation and related technologies.
Cover Letter: Outline your technical expertise, experience in machine learning model development, and any past achievements in AI image segmentation projects. Highlight your ability to work with large datasets and your approach to solving complex image segmentation problems.
Portfolio (optional): If applicable, share links to GitHub repositories, published papers, or any projects that demonstrate your capabilities in AI image segmentation.

This role offers an opportunity to work with a forward-thinking company, develop cutting-edge AI models, and contribute to high-impact projects. Apply today to join our innovative team and take your career in AI to the next level!

For more information about the company or similar roles in AI and machine learning, feel free to visit our AI Engineering Careers Page.

Job Category: Medical Device

Job Type: Full Time

Job Location: Chicago

AI Image Segmentation Engineer – Chicago, IL