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Postdoctoral In Reinforcement Learning Jobs in Virginia

Autonomy Engineer

Chantilly, VA · Hybrid

$140K - $190K/yr

Experience with reinforcement learning libraries such as RLLib or Gym * Experience with development in Python * Experience with space-based hardware and software, or adjacent aerospace experience

In this role, you will work with cutting-edge technologies to design, develop, and deploy machine ... Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement ...

Senior Machine Learning Engineer

Mclean, VA · On-site

$105K - $145K/yr

Supervised, unsupervised, and reinforcement learning * Neural networks, decision trees, ensemble ... Bachelor's degree in Computer Science, Engineering, Applied Mathematics, or a related field * 7+ ...

Senior Machine Learning Engineer

Mclean, VA · On-site

$105K - $145K/yr

Supervised, unsupervised, and reinforcement learning * Neural networks, decision trees, ensemble ... Bachelor's degree in Computer Science, Engineering, Applied Mathematics, or a related field * 7+ ...

In this role, you will work with cutting-edge technologies to design, develop, and deploy machine ... Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement ...

Senior Machine Learning Engineer

Mclean, VA · On-site

$105K - $145K/yr

Supervised, unsupervised, and reinforcement learning * Neural networks, decision trees, ensemble ... Bachelor's degree in Computer Science, Engineering, Applied Mathematics, or a related field * 7+ ...

In this role, you will work with cutting-edge technologies to design, develop, and deploy machine ... Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement ...

Machine Learning Engineer

Reston, VA · On-site

$110 - $170/hr

In this role, you will work with cutting-edge technologies to design, develop, and deploy machine ... Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement ...

Showing results 41-60

Postdoctoral In Reinforcement Learning information

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 the key skills and qualifications needed to thrive as a postdoctoral researcher in reinforcement learning?

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 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 popular job titles related to Postdoctoral In Reinforcement Learning jobs in Virginia?

For Postdoctoral In Reinforcement Learning jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Postdoctoral In Reinforcement Learning jobs in Virginia look for?

The top searched job categories for Postdoctoral In Reinforcement Learning jobs in Virginia are:

What cities in Virginia are hiring for Postdoctoral In Reinforcement Learning jobs?

Cities in Virginia with the most Postdoctoral In Reinforcement Learning job openings:

$143K - $229K/yr

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Medical, Retirement, PTO

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Blue Cross and Blue Shield of North Carolina rating

7.8

Company rating: 7.8 out of 10

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195th of 315 rated insurance


Job description

Job Description

Serve as the senior AI/ML scientist to identify, research, and develop transformational predictive, prescriptive, and Generative AI (GenAI) solutions that translate structured and unstructured data into sound organizational decisions. Senior AI/ML scientist will combine statistical expertise, programming skills, and data science knowledge to create impactful self-learning applications and collaborate with multidisciplinary teams to integrate AI technologies into real-world systems and solutions to achieve business goals.

What You Will Do

  • Own delivery of large and/or complex machine learning (ML), deep learning (DL), and Generative AI (GenAI) systems with self-learning capabilities that can adapt and evolve over time.

  • Design, implement, and evaluate artificial intelligence (AI) systems that can be used in production environments to meet business needs.

  • Apply prescriptive analytics techniques such as optimization, recommendation systems, and reinforcement learning to business problems.

  • Lead in the development and testing of appropriate ML algorithms, design & conduct experiments, collect and analyze data, and optimize performance of ML algorithms.

  • Stay updated with the advancements in artificial intelligence, machine learning, and generative AI methods and adapt new methods to effectively solve business problems.

  • Benchmark against existing machine learning methods and analyze results to identify strengths, weaknesses, and areas for improvement.

  • Develop prototypes and proof-of-concept implementations to demonstrate the feasibility and potential of new AI technologies including Generative AI.

  • Lead consultation sessions with business partners to distill the business needs and provide technical guidance on predictive and prescriptive AI approaches, ensuring alignment with business goals.

  • Drive continuous improvement by experimenting with novel techniques and refining existing models.

  • Leverage deep knowledge of software engineering principles in constructing sophisticated ML models and refining existing systems.

  • Identify actionable insights, suggest recommendations, and influence business direction by effectively communicating results to cross functional groups.

What You Bring

  • Bachelor's degree or advanced degree (where required)

  • 5+ years of experience in related field.

  • In lieu of degree, 7+ years of experience in related field.

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Salary Range

At Blue Cross NC, we take great pride in a fair and equitable compensation package that reflects market-price and our starting salaries are typically planned near the middle of the range listed. Compensation decisions are driven by factors including experience and training, specialized skill sets, licensure and certifications and other business and organizational needs.Our base salary is part of a robust Total Rewards package that includes an Annual Incentive Bonus*, 401(k) with employer match, Paid Time Off (PTO), and competitive health benefits and wellness programs.

*Based on annual corporate goal achievement and individual performance.

$143,616.00 - $229,786.00

Skills

Artificial Intelligence (AI), Benchmarking, Best Practices Development, Data Analysis, Data Science, Data Visualization, Deep Learning Algorithms, Machine Learning (ML), Machine Learning Methods, Predictive Algorithms, Prescriptive Analytics, Reinforcement Learning, Statistical Models, Statistics

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