Deep Learning Engineer - Reinforcement Learning

Placements24; Queenstown; On-site; NZD 120,000 - 180,000; Full time

Benefits offered by this job

Health insurance

Retirement contributions

Generous paid time off

Training & conference opportunities

Access to advanced computing resources

Job summary

Placements24 is seeking a Deep Learning Engineer with Reinforcement Learning expertise to join its R&D team in Queenstown. You will design, implement, and optimize RL algorithms, and work with state-of-the-art simulation environments and real-world data to push the boundaries of autonomous systems research.

The role requires a strong foundation in deep learning and RL, proficient Python coding, and collaboration with researchers to advance intelligent agents.

Qualifications

• Master's or PhD in CS/AI/ML or related field.
• Proven experience developing and applying reinforcement learning algorithms.
• Strong Python and DL framework skills (TensorFlow, PyTorch).
• Familiarity with RL simulators (OpenAI Gym, MuJoCo).
• Excellent analytical and collaboration abilities.

Responsibilities

• Design, develop, and implement deep RL algorithms (e.g., DQN, PPO, SAC).
• Train and fine-tune RL models on simulations and real-world data.
• Benchmark RL agents in complex environments.
• Collaborate with researchers to define RL problems and objectives.
• Write clean, documented Python code and contribute to deployments.
• Stay up-to-date with the latest DL and RL research.
• Participate in team meetings, code reviews, and knowledge sharing.

Skills

Reinforcement learning experience

Python programming

Strong analytical thinking

Team collaboration

Education

Master's or PhD in Computer Science / AI / ML

Tools

TensorFlow

PyTorch

OpenAI Gym

MuJoCo

C++

Job description

About the Role

Our client, a pioneer in autonomous systems research, is seeking a highly skilled Deep Learning Engineer with expertise in Reinforcement Learning (RL) to join their dedicated R&D team in Queenstown, Eastern Cape . This role is instrumental in advancing the capabilities of intelligent agents and complex decision-making systems. You will be responsible for designing, implementing, and optimizing RL algorithms for real-world applications. The ideal candidate will possess a strong theoretical foundation in deep learning and reinforcement learning, coupled with practical experience in developing and deploying sophisticated AI models. This is a unique opportunity to contribute to groundbreaking research and development in a dynamic field. You will work with state-of-the-art simulation environments and real-world data, pushing the boundaries of AI. We value a collaborative spirit and a passion for innovation.

Key Responsibilities

• Design, develop, and implement deep reinforcement learning algorithms (e.g., DQN, PPO, SAC).
• Train and fine-tune RL models using various simulation platforms and real-world datasets.
• Develop novel approaches to address challenges in exploration, exploitation, and credit assignment.
• Collaborate with researchers and engineers to define RL problem statements and objectives.
• Evaluate and benchmark the performance of RL agents in complex environments.
• Optimize RL algorithms for computational efficiency and scalability.
• Write clean, well-documented, and maintainable code in Python.
• Contribute to the deployment of RL solutions in relevant applications.
• Stay current with the latest research and advancements in deep learning and reinforcement learning.
• Participate in team meetings, code reviews, and knowledge sharing sessions.

Requirements

• Master's or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Proven experience in developing and applying reinforcement learning algorithms.
• Strong programming skills in Python and deep learning frameworks (e.g., TensorFlow, PyTorch).
• Solid understanding of deep learning concepts, including neural network architectures and optimization techniques.
• Familiarity with RL simulation environments (e.g., OpenAI Gym, MuJoCo) and libraries.
• Experience with data analysis and visualization tools.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and collaboration abilities.
• Experience with C++ is a plus.
• Ability to work effectively in a team-oriented research environment in Queenstown, Eastern Cape .

Benefits

• Our client offers a competitive salary and a comprehensive benefits package, including excellent health insurance, retirement contributions, and generous paid time off.
• They are committed to fostering professional growth through training programs, conference attendance, and opportunities for research publication.
• Employees have access to advanced computing resources and work on challenging, cutting-edge AI projects.
• The non-remote structure in Queenstown, Eastern Cape ensures strong team cohesion and direct collaboration.