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Postdoctoral In Reinforcement Learning Jobs in Illinois

IT360, Inc.

AI Engineer

Peoria, IL

Strong programming skills in Python (preferred), Java, or C++. * Experience with machine learning ... Familiarity with NLP, computer vision, reinforcement learning, and large language models (LLMs)

Braze

Senior Lead AI Solutions Consultant

Chicago, IL · On-site

$124K - $186K/yr

An expert in machine learning: You have a solid grasp of machine learning, including a familiarity with reinforcement learning * Mar-tech savvy: You understand the marketing technology ecosystem and ...

Braze

Senior Lead AI Solutions Consultant

Chicago, IL · On-site

$124K - $186K/yr

An expert in machine learning: You have a solid grasp of machine learning, including a familiarity with reinforcement learning * Mar-tech savvy: You understand the marketing technology ecosystem and ...

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Postdoctoral In Reinforcement Learning information

What is the difference between Postdoctoral In Reinforcement Learning vs Postdoctoral In Machine Learning?

AspectPostdoctoral In Reinforcement LearningPostdoctoral In Machine Learning
Required CredentialsPhD in Computer Science, AI, or related field; strong programming skills; research experience in reinforcement learningPhD in Computer Science, AI, or related field; strong programming skills; research experience in machine learning
Work EnvironmentAcademic labs, research institutions, industry R&D teams focused on reinforcement learning applicationsAcademic labs, research institutions, industry R&D teams working on various machine learning techniques
Industry UsagePrimarily in AI research, robotics, gaming, and autonomous systemsBroader applications including data analysis, predictive modeling, and AI research

Postdoctoral In Reinforcement Learning specializes in research related to decision-making algorithms and autonomous systems, whereas Postdoctoral In Machine Learning covers a wider range of AI techniques. Both roles require similar credentials but differ in focus and application areas.

What are the key skills and qualifications needed to thrive as a Postdoctoral Researcher in Reinforcement Learning, and why are they important?

To thrive as a Postdoctoral Researcher in Reinforcement Learning, you need a PhD in computer science or a related field, with deep expertise in machine learning, statistics, and algorithm development. Proficiency in programming languages such as Python, experience with deep learning frameworks (e.g., TensorFlow or PyTorch), and familiarity with reinforcement learning libraries are typically required. Strong analytical thinking, problem-solving ability, collaboration, and scientific communication skills help you excel in research teams and publish impactful work. These competencies are vital to advancing state-of-the-art research, developing novel algorithms, and contributing to the academic and industrial progress in AI.

What are some common challenges faced by postdoctoral researchers in reinforcement learning, and how can they be addressed?

Postdoctoral researchers in reinforcement learning often face challenges such as balancing independent research projects with collaborative work, staying up-to-date with rapidly evolving literature, and managing the pressure to publish in top conferences. Effective time management, regular engagement with the research community through seminars and workshops, and seeking mentorship from senior colleagues can help address these challenges. Additionally, collaborating with interdisciplinary teams can offer fresh perspectives and support, making it easier to navigate complex research problems.

What is a Postdoctoral Researcher in Reinforcement Learning?

A Postdoctoral Researcher in Reinforcement Learning is an individual who has completed a PhD and conducts advanced research in the field of reinforcement learning, a branch of artificial intelligence focused on how agents take actions in environments to maximize rewards. These researchers often work in academic, industrial, or governmental research settings, collaborating on projects that advance the theoretical foundations or practical applications of reinforcement learning. Their responsibilities may include designing experiments, developing algorithms, publishing papers, and mentoring graduate students.
What are popular job titles related to Postdoctoral In Reinforcement Learning jobs in Illinois? For Postdoctoral In Reinforcement Learning jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Postdoctoral In Reinforcement Learning jobs in Illinois look for? The top searched job categories for Postdoctoral In Reinforcement Learning jobs in Illinois are:
What cities in Illinois are hiring for Postdoctoral In Reinforcement Learning jobs? Cities in Illinois with the most Postdoctoral In Reinforcement Learning job openings:
Postdoctoral In Reinforcement Learning jobs near you
AI Engineer

AI Engineer

IT360, Inc.

Peoria, IL

Full-time

Medical, Life, Retirement, PTO

Posted 14 days ago

Job description

Job Title: AI Engineer

Location: Peoria, IL

Work Environment: IN-OFFICE ONLY (Peoria, IL) Not a remote or hybrid position.

Job Type: Full-Time


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About the Role

IT360, Inc. is seeking a highly skilled and innovative AI Engineer to join our growing team. This strategic, client-facing role is responsible for designing, developing, and leading deployment of AI-driven solutions and automations that address complex business challenges for both internal operations and external clients. You'll work with a variety of machine learning, automations, and scripting technologies to deliver intelligent, secure, and scalable solutions tailored to client needs.


Key Responsibilities

  • Design and develop scalable AI/ML models to solve real-world problems across various domains.
  • Collaborate with clients to identify AI opportunities and define solution requirements.
  • Build and maintain end-to-end machine learning pipelines, from data ingestion and preprocessing to model training, evaluation, and deployment.
  • Integrate AI solutions into existing systems and platforms, ensuring performance, reliability, and scalability.
  • Monitor and improve the performance of deployed models through continuous evaluation and retraining.
  • Stay current with the latest advancements in AI/ML research and tools, and apply them to enhance solution effectiveness.
  • Document processes, models, and systems to ensure transparency and reproducibility.
  • Design and implement automations to streamline internal workflows and enhance client-facing services.


Additional Duties

  • Collaborate with cross-functional teams to ensure seamless solution delivery.
  • Provide high-quality customer service and maintain strong client relationships.
  • Understand client business needs and align technology solutions accordingly.
  • Accurately track time, tasks, and expenses in the ticketing system.
  • Participate in customer interviews, feedback loops, and solution ideation.


Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field - or equivalent experience (e.g., GitHub projects, personal portfolio).
  • Strong programming skills in Python (preferred), Java, or C++.
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Proficiency in data manipulation and analysis using Pandas, NumPy, and SQL.
  • Experience with cloud platforms (AWS, Azure, Google Cloud, OpenAI) and MLOps tools.
  • Solid understanding of algorithms, data structures, and software engineering principles.
  • Ability to work independently and collaboratively, with a strong sense of ownership and self-management.
  • Familiarity with NLP, computer vision, reinforcement learning, and large language models (LLMs).
  • Knowledge of data privacy, model interpretability, and ethical AI practices.
  • Contributions to open-source AI projects or published research are a plus.


Skills & Technologies

  • Scripting & Automation: PowerShell, Python (Jinja), Power Automate, REWST, Zapier
  • APIs: REST (required), SOAP (optional), OpenAPI spec, Postman
  • AI Techniques: Retrieval-Augmented Generation (RAG), AI scoring (Model Performance Metrics), reinforcement learning
  • LLM Platforms: OpenAI, Claude, Gemini
  • Microsoft 365 Stack: CoPilot, Power Automate, Function Apps, Email integrations
  • Cloud & Serverless: Azure Function Apps


Benefits (subject to eligibility and length of employment)

  • Health insurance allowance up to $400/month
  • Employer-paid group life insurance policy valued at $100,000
  • 3% employer match on retirement savings plan
  • Aflac individual accident insurance
  • High-speed internet reimbursement up to $40/month
  • $40/month cellular phone allowance
  • 8 paid holidays annually
  • Paid vacation: 5 days/year to start, increasing to 10 days/year after 3 years of service
  • Access to Safe Ride Home Program (Uber ridesharing)

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