Harman

Job Responsibilities

The Reinforcement Learning Application Developer role will primarily focus on defining requirements and designing solutions for artificial intelligence and machine learning applications with a specific emphasis on reinforcement learning. This position will actively engage with project teams to strategize, establish, and execute comprehensive requirements gathering and management processes tailored for RL  projects.

Education

Graduate or master’s in computer science or engineering with 5+ years of experience

Experience/Qualifications

Required Technical Skills/Education:

• Reinforcement Learning: Proven experience with reinforcement learning algorithms, including Q-Learning, Deep Q-Networks (DQN), Policy Gradients, Actor-Critic methods, and Proximal Policy Optimization (PPO).
• Machine Learning Libraries: Knowledge of libraries such as TensorFlow, PyTorch, and scikit-learn is crucial for implementing machine learning algorithms and reinforcement learning solutions.
• Deep Learning Frameworks: Proficiency in building and training deep neural networks using frameworks like TensorFlow and PyTorch is highly desirable.
• Data Processing Tools: Proficiency in data processing tools such as Pandas and NumPy for data manipulation, cleaning, and feature engineering.
• Cloud Platforms: Familiarity with cloud platforms like AWS, Azure, or Google Cloud Platform.
• Reinforcement Learning Environments: Experience with simulation environments such as OpenAI Gym, Unity ML-Agents, and other custom simulation environments.
• Model Evaluation: Experience with model evaluation techniques such as cross-validation, hyperparameter tuning, and understanding of metrics specific to reinforcement learning like average reward, cumulative reward, and convergence rate.
• Coding Experience: Strong coding experience in Python, with extensive use of libraries like PyTorch, TensorFlow, and OpenAI Gym.
• Communication Skills: Fluent in English (both written and spoken), with solid technical writing, presentation, and communication skills.

Preferred Technical Skills/Education:

• Reinforcement Learning Projects: Hands-on experience with implementing and deploying reinforcement learning models in real-world applications.
• Cloud Deployments: Experience with AWS and Azure deployments for machine learning workflows, including the use of services like AWS SageMaker RL  and Azure Machine Learning – reinforcement learning.
• Simulation Environments: Proficiency in creating and managing complex simulation environments for training reinforcement learning agents.
• Continuous Learning: Familiarity with continuous learning and online learning paradigms in reinforcement learning.

Additional Comments

This candidate must be highly motivated, organized, self-driven, and able to function in a global team environment (USA, China, India, and Europe). The ideal candidate will demonstrate strong problem-solving and analytical thinking skills.