Deep Reinforcement Learning Engineer – Research & Deployment

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

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.