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Machine Learning Object Detection Jobs in Chicago, IL

The Aspen Group

Senior Site Reliability Engineer

Chicago, IL · On-site

$58.75 - $78/hr

Develop and manage Service Level Objectives (SLOs) and Service Level Indicators (SLIs) using machine learning anomaly detection to ensure systems meet reliability targets. * Drive improvements in ...

The Aspen Group

Senior Site Reliability Engineer

Chicago, IL · On-site

$58.75 - $78/hr

Develop and manage Service Level Objectives (SLOs) and Service Level Indicators (SLIs) using machine learning anomaly detection to ensure systems meet reliability targets. * Drive improvements in ...

Vizient, Inc.

Lead Data Scientist

Chicago, IL

$117.60K - $206K/yr

... detection, and natural language processing required. Demonstrated advanced knowledge of data science methodologies, statistical modeling, machine learning, and generative AI techniques required.

Vizient

Lead Data Scientist

Chicago, IL · On-site

$117.60K - $206K/yr

... detection, and natural language processing required. * Demonstrated advanced knowledge of data science methodologies, statistical modeling, machine learning, and generative AI techniques required.

Dime Line Trading

Quantitative Developer

Chicago, IL

... and machine learning models from this data * Any amount of experience testing and improving low ... Any amount of experience developing and maintaining Object Oriented codebases/libraries * Any ...

Tata Consultancy Service Limited

AI Architect

Chicago, IL · On-site

$100K - $150K/yr

Strong experience in Machine Learning, statistical modeling, and applied analytics. * Hands on ... Performance and data drift detection * Support multi tenant AI platforms used by multiple analytics ...

Tata Consultancy Service Limited

AI Architect

Chicago, IL · On-site

$100K - $150K/yr

Strong experience in Machine Learning, statistical modeling, and applied analytics. * Hands on ... Performance and data drift detection * Support multi tenant AI platforms used by multiple analytics ...

Paylocity

Staff Data Scientist

Schaumburg, IL · On-site

... machine learning solutions to meet client needs in domains ranging from NLP and supervised learning to time series forecasting and anomaly detection. The team is focused on building high impact ...

Paylocity

Staff Data Scientist

Schaumburg, IL · On-site

... machine learning solutions to meet client needs in domains ranging from NLP and supervised learning to time series forecasting and anomaly detection. The team is focused on building high impact ...

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All JobsMachine Learning Object Detection JobsMachine Learning Object Detection Jobs in Chicago, IL

Machine Learning Object Detection information

See Chicago, IL salary details

$32.5K

$132.7K

$199.3K

How much do machine learning object detection jobs pay per year?

As of May 30, 2026, the average yearly pay for machine learning object detection in Chicago, IL is $132,651.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,600.00 and $159,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Object Detection Engineer, and why are they important?

To excel as a Machine Learning Object Detection Engineer, you need a solid background in computer science, mathematics, and deep learning principles, often backed by a relevant degree and experience in computer vision. Familiarity with frameworks like TensorFlow, PyTorch, and OpenCV, as well as experience with annotation tools and GPU computing, is typically required. Strong problem-solving abilities, attention to detail, and effective communication are vital soft skills for collaborating with cross-functional teams and addressing complex challenges. These competencies ensure accurate model development, efficient deployment, and continual improvement of object detection systems in real-world applications.

What are some common challenges faced when working on machine learning object detection projects?

One of the main challenges in machine learning object detection roles is dealing with the quality and quantity of annotated data, as accurate labeling is essential for model performance. Another common challenge is managing variations in object scale, lighting, and occlusion within real-world images, which can affect detection accuracy. Additionally, balancing model accuracy with computational efficiency—especially for real-time applications—often requires careful model selection and optimization. Collaboration with data engineers and domain experts is also typical to ensure data relevance and model applicability.

What is machine learning object detection?

Machine learning object detection is a field within artificial intelligence that focuses on identifying and locating objects within images or videos. It uses algorithms and deep learning models, such as convolutional neural networks (CNNs), to analyze visual data and predict the presence and position of various objects. Object detection is widely used in applications like autonomous vehicles, security surveillance, and image search. The process typically involves training models on labeled datasets so they can accurately detect and classify multiple objects in complex scenes.
What are popular job titles related to Machine Learning Object Detection jobs in Chicago, IL? For Machine Learning Object Detection jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Machine Learning Object Detection jobs in Chicago, IL look for? The top searched job categories for Machine Learning Object Detection jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Machine Learning Object Detection jobs? Cities near Chicago, IL with the most Machine Learning Object Detection job openings:
Machine Learning Object Detection jobs near you

Senior Site Reliability Engineer

The Aspen Group

Chicago, IL • On-site

$58.75 - $78/hr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 29 days ago

Job description

The Aspen Group (TAG) is one of the largest and most trusted retail healthcare business support organizations in the U.S. and has supported over 20,000 healthcare professionals and team members with close to 1,500 health and wellness offices across 48 states in four distinct categories: dental care, urgent care, medical aesthetics, and animal health. Working in partnership with independent practice owners and clinicians, the team is united by a single purpose: to prove that healthcare can be better and smarter for everyone. TAG provides a comprehensive suite of centralized business support services that power the impact of five consumer-facing businesses: Aspen Dental, ClearChoice Dental Implant Centers, WellNow Urgent Care, Chapter Aesthetic Studio, and Lovet Pet Health Care. Each brand has access to a deep community of experts, tools and resources to grow their practices, and an unwavering commitment to delivering high-quality consumer healthcare experiences at scale.
As a Senior Site Reliability Engineer (SRE) at TAG - The Aspen Group, you will be responsible for ensuring the reliability, performance, and scalability of our core systems. This role involves proactively building and managing, monitoring solutions, lead incident response, and continuously optimizing system performance to exceed business objectives. We are actively integrating AI and machine learning into our operational workflows, and you will be on the front lines, leveraging intelligent automation and machine learning to build a proactive resilient infrastructure. This is an opportunity to go beyond SRE by applying cutting-edge technology to solve complex reliability challenges.
Responsibilities:
Intelligent Site Reliability Engineering:
  • Design and build highly scalable and resilient systems to support our applications and services, incorporating predictive analytics to anticipate reliability risks.
  • Develop and manage Service Level Objectives (SLOs) and Service Level Indicators (SLIs) using machine learning anomaly detection to ensure systems meet reliability targets.
  • Drive improvements in system reliability, availability, and performance through proactive measures, automation, and intelligent failure prediction.

Advanced Observability:
  • Implement and manage comprehensive monitoring and alerting solutions, integrating with intelligent observability platforms that reduce alert noise and correlate events.
  • Develop and maintain dashboards and reporting tools that provide data-driven insights for actionable troubleshooting recommendations and performance optimization.
  • Evaluate and integrate advanced monitoring tools and operational intelligence platforms to enhance observability and root cause identification.

Proactive Incident Management:
  • Lead and participate in incident response efforts, using intelligent log analysis and automated event correlation to speed up troubleshooting and root cause identification.
  • Develop and maintain incident management processes incorporating automated decision support systems to improve response times and minimize service disruptions.
  • Conduct post-incident reviews, using automated pattern recognition and trend analysis to identify systemic issues and implement preventive measures.

Performance and Capacity Optimization:
  • Analyze performance metrics and logs, supported by advanced observability tools, to detect bottlenecks and inefficiencies.
  • Collaborate with development teams to implement automated profiling and optimization recommendations for code and infrastructure improvements.
  • Perform capacity planning using machine learning forecasting models to ensure systems can handle current and future loads.

Automation and Process Improvement:
  • Develop and implement automation solutions, including intelligent runbook automation, self-healing systems, and automated incident triage.
  • Identify and drive process improvements by applying machine learning to operational data for continuous optimization.
  • Maintain documentation that includes automation and machine learning guidelines for monitoring, incident management, and SRE best practices.

Collaboration and Communication:
  • Work closely with engineering, operations, and product teams to align reliability and monitoring goals, including automation adoption strategies.
  • Communicate effectively with stakeholders, providing regular updates on system health, incidents, performance improvements, and data-driven insights.
  • Foster a culture of collaboration, knowledge sharing, and automation best practices within the team and across the organization.

Requirements:
  • Bachelor's degree in computer science or a related technical field.
  • At least 5 years of experience in Site Reliability Engineering or a similar role.
  • Strong proficiency in at least one programming language such as Python, Go, or C#
  • Demonstrated experience applying machine learning and automation to operational workflows such as monitoring, alerting and incident response.
  • Expertise with infrastructure as code tools such as Terraform
  • Proven experience working and monitoring container environments such as Cloud Run and Kubernetes.
  • Hands-on experience using and working within an Azure, AWS, and GCP environment (GCP preferred)
  • Strong understanding of networking, distributed systems, and cloud infrastructure.
  • Familiarity with intelligent monitoring platforms and operational analytics tools such as Prometheus, Grafana, OpenSearch, Sentry, Google Cloud Observability
  • Excellent problem-solving skills and the ability to work independently and as part of a team.
  • Experience with incident management, root cause analysis, and automated operational workflows.

Annual pay range: $129,000-$160,000
A generous benefits package that includes paid time off, health, dental, vision, and 401(k) savings plan with match

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