Deskripsi Pekerjaan
Are you passionate about building the future of autonomous systems and simulation technology? PLT Engineering is seeking a highly skilled Senior Machine Learning Engineer (Simulation) to join our elite team in Singapore. In this role, you will be at the forefront of developing sophisticated simulation environments that power complex decision-making models. You will bridge the gap between theoretical ML research and real-world application, ensuring our systems are robust, scalable, and highly performant.
You will work with cross-functional teams to design high-fidelity simulation frameworks, enabling the rapid testing and iteration of ML algorithms. We are looking for an engineer who thrives in high-stakes environments and enjoys solving challenging problems in synthetic data generation and environment modeling. If you are a self-starter with a deep passion for cutting-edge AI, we want to hear from you.
Tanggung Jawab
- Design and implement scalable high-fidelity simulation frameworks for autonomous system testing.
- Develop and optimize machine learning models to generate synthetic data that mirrors real-world complexity.
- Collaborate with cross-functional research and product teams to integrate simulation results into the production pipeline.
- Conduct rigorous performance analysis and validation of ML models within simulated environments.
- Architect robust infrastructure to support large-scale simulation deployments and parallel computing.
- Mentor junior engineers and contribute to the growth of our technical engineering culture.
- Stay abreast of industry trends in generative AI, reinforcement learning, and simulation tech.
Kualifikasi
- Master’s or PhD degree in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field.
- 5+ years of professional experience in Machine Learning engineering, with a focus on simulation or robotics.
- Proficiency in Python and C++ for high-performance computing applications.
- Strong experience with deep learning frameworks such as PyTorch or TensorFlow.
- Deep understanding of reinforcement learning (RL) and synthetic data generation techniques.
- Experience with cloud computing platforms (AWS/GCP/Azure) and containerization tools (Docker/Kubernetes).
- Excellent communication and problem-solving skills with a collaborative mindset.