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Senior Reinforcement Learning Jobs in Georgia (NOW HIRING)

Extensive experience with various machine learning techniques (e.g., supervised, unsupervised, reinforcement learning, deep learning) and their practical applications. * Strong understanding of ...

Lead Data Scientist

Dallas, GA · On-site

$161 - $270/hr

... Reinforcement Learning, Search Algorithms, and AI- Knowledge Graphs. * Visualization and ... with senior leadership. Supervisor No TCP Career Step Differentiator: Performs very complex data ...

New

Lead Data Scientist

Atlanta, GA · On-site

$160K - $270K/yr

... Reinforcement Learning, Search Algorithms, and AI- Knowledge Graphs. • Visualization and ... senior leadership. Supervisor: No TCP Career Step Differentiator: Performs very complex data ...

... Reinforcement Learning, Search Algorithms, and AI- Knowledge Graphs. Visualization and ... senior leadership. Supervisor: No TCP Career Step Differentiator: Performs very complex data ...

This hybrid, individual contributor role reports to the Senior Manager, Commercial Capability and ... reinforcement. * Support sales tool onboarding for new hires, including access requests, CRM setup ...

Head of Enablement

Atlanta, GA · On-site

$151K - $189K/yr

Reporting to the SVP of GTM Operations, you will lead the team responsible for onboarding ... Own the company-wide execution, coaching, and reinforcement of MEDDPICC and frameworks across the ...

Showing results 41-60

Senior Reinforcement Learning information

What does a senior reinforcement learning engineer do?

A Senior Reinforcement Learning Engineer designs, develops, and implements advanced machine learning algorithms that enable systems to learn optimal behaviors through trial and error. They work on complex problems such as robotics, game AI, recommendation systems, and automated decision-making. In addition to coding and model development, they often lead research initiatives, collaborate with cross-functional teams, and mentor junior engineers. Their role requires deep knowledge of reinforcement learning theory, practical experience with machine learning frameworks, and strong programming skills.

What are some common challenges faced by senior reinforcement learning professionals when deploying models in real-world environments?

Senior Reinforcement Learning professionals often encounter challenges such as ensuring model robustness when transferring algorithms from simulated to real-world environments, handling limited or noisy data, and managing the computational demands of training complex models. Additionally, safety and interpretability are critical, as real-world deployments can have significant impacts if models behave unpredictably. Close collaboration with domain experts and engineering teams is essential to address these challenges and ensure successful, scalable deployments.

What are the key skills and qualifications needed to thrive as a senior reinforcement learning engineer, and why are they important?

To thrive as a Senior Reinforcement Learning Engineer, you need deep expertise in machine learning, reinforcement learning algorithms, and programming languages such as Python, often supported by an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and RL-specific libraries, as well as experience with high-performance computing and cloud platforms, is typically required. Strong problem-solving abilities, collaboration, and communication skills help distinguish top performers in this role. These skills ensure the development of efficient, robust RL models and effective teamwork on complex AI projects.

What is the difference between Senior Reinforcement Learning vs Data Scientist?

AspectSenior Reinforcement LearningData Scientist
Required CredentialsAdvanced degrees in CS, ML, or related fields; experience with RL frameworksDegree in CS, Statistics, or related; strong analytical skills
Work EnvironmentResearch labs, AI teams, tech companies focusing on ML projectsBusiness analytics, data analysis, and modeling in various industries
Employer & Industry UsageTech firms, AI startups, research institutionsFinance, healthcare, marketing, tech, and more

While both roles require strong analytical skills and technical knowledge, Senior Reinforcement Learning specialists focus on developing RL algorithms and models, often in AI research settings. Data Scientists analyze data to inform business decisions across industries. The roles overlap in data handling and programming but differ in their core focus and application areas.

What are the most commonly searched types of Reinforcement Learning jobs in Georgia?

The most popular types of Reinforcement Learning jobs in Georgia are:

What cities in Georgia are hiring for Senior Reinforcement Learning jobs?

Cities in Georgia with the most Senior Reinforcement Learning job openings:

Full-time

Medical, Retirement, PTO

Posted 21 days ago


Job description

ABOUT THIS POSITION

Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse "big data" sources to generate actionable insights and solutions for client services and product enhancement. Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers. Incumbents whose primary role is technical and focused on data storage, warehousing and systems architecture should be matched to Database Engineering or Storage Engineering. Incumbents whose focus is the quantitative analysis of complex business problems and issues using data from internal and external sources to provide insight to decision-makers should be matched to Business Intelligence. Incumbents whose primary role is technical and focused on designing and building system-generated reports, reporting tools and dashboards for data generation should be matched to Data Informatics. Incumbents whose focus is primarily on experimental design and advanced or complex statistical analysis and modeling of datasets should be matched to Statistician/Mathematician. This is a product engineering role in which employees work with multiple types of business data. Incumbents whose focus is primarily on analysis and modeling of financial, marketing or pricing data should be matched to Finance, Market Research or Pricing as appropriate. May be internal operations-focused or external client-focused, working in conjunction with Professional Services and outsourcing functions.

WHAT YOU'LL DO

* Lead the design, development, and implementation of sophisticated machine learning models and predictive analytics solutions to solve critical business problems.
* Mentor and guide junior data scientists, fostering a culture of excellence and continuous learning within the team.
* Collaborate with cross-functional teams (engineering, product, business stakeholders) to define data science project requirements, scope, and deliverables.
* Conduct in-depth data exploration, analysis, and visualization to identify trends, patterns, and anomalies, presenting findings clearly and concisely to diverse audiences.
* Develop and maintain robust data pipelines and infrastructure in collaboration with data engineers to ensure data quality, accessibility, and integrity.
* Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence, evaluating and recommending new technologies and methodologies.
* Contribute to the strategic direction of Waystar's data science initiatives, identifying opportunities for innovation and impact.
* Champion data-driven decision-making throughout the company, educating and influencing stakeholders on the power of data science.
* Evaluate and select appropriate statistical methods and machine learning algorithms for various business challenges, ensuring rigor and validity.

WHAT YOU'LL NEED

* Master's or Ph.D. in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
* 8+ years of progressive experience in data science, with a proven track record of delivering impactful data-driven solutions in a fast-paced environment.
* Expert-level proficiency in Python and/or R for data manipulation, statistical analysis, and machine learning model development.
* Extensive experience with various machine learning techniques (e.g., supervised, unsupervised, reinforcement learning, deep learning) and their practical applications.
* Strong understanding of statistical modeling, experimental design, hypothesis testing, and causal inference.
* Proficiency in SQL for data querying and manipulation, with experience working with large-scale datasets.
* Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop) is highly desirable.
* Excellent communication, presentation, and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders.
* Demonstrated ability to lead projects, mentor team members, and drive successful outcomes.
* Prior experience in the healthcare technology or financial services industry is a plus.

ABOUT WAYSTAR

Through a smart platform and better experience, Waystar helps providers simplify healthcare payments and yield powerful results throughout the complete revenue cycle.

Waystar's healthcare payments platform combines innovative, cloud-based technology, robust data, and unparalleled client support to streamline workflows and improve financials so providers can focus on what matters most: their patients and communities. Waystar is trusted by 1M+ providers, 1K+ hospitals and health systems, and is connected to over 5K commercial and Medicaid/Medicare payers. We are deeply committed to living out our organizational values: honesty; kindness; passion; curiosity; fanatical focus; best work, always; making it happen; and joyful,optimistic & fun.

Waystar products have won multiple Best in KLAS or Category Leader awards since 2010 and earned multiple #1 rankings from Black Book surveys since 2012. The Waystar platform supports more than 500,000 providers, 1,000 health systems and hospitals, and 5,000 payers and health plans. For more information, visit waystar.comor follow @Waystaron Twitter.

WAYSTAR PERKS

  • Competitive total rewards (base salary + bonus, if applicable)
  • Customizable benefits package (3 medical plans with Health Saving Account company match)
  • We offer generous paid time off for our non-exempt team members, starting with 3 weeks +13 paid holidays, including 2 personal floating holidays. We also offer flexible time off for our exempt team members + 13 paid holidays
  • Paid parental leave (including maternity + paternity leave)
  • Education assistance opportunities and free LinkedIn Learning access
  • Free mental health and family planning programs, including adoption assistance and fertility support
  • 401(K) program with company match
  • Pet insurance
  • Employee resource groups

Waystar is proud to be an equal opportunity workplace. We celebrate, value, and support diversity and inclusion. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, marital status, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.