Remote Senior Deep Learning Engineer — Equity & AI Innovation

Placements24; Richards Bay; Hybride; ZAR 1 990 000 - 2 985 000; Plein temps

Avantages offerts par ce poste

Equity options

Full remote work

Health, dental, vision insurance

Résumé du poste

Placements24 is seeking a Senior Deep Learning Engineer to join their fully remote team and drive breakthroughs in AI. You will design, implement, and optimize deep learning models for diverse applications, collaborating with research scientists and engineers across time zones.

The role emphasizes research, development, and scalable training/inference pipelines, with a focus on state-of-the-art results and production-ready code.

Qualifications

• Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field with a focus on deep learning.
• 5+ years of professional experience in deep learning research and development.
• Expertise in deep learning frameworks such as TensorFlow, PyTorch, or JAX.
• Strong proficiency in Python and experience with libraries for scientific computing and data analysis.
• Proven ability to work effectively in a remote, self-directed environment.

Responsabilités

• Design, develop, and optimize deep learning models for applications including computer vision and NLP.
• Implement and fine-tune neural network architectures for performance and efficiency.
• Conduct experiments, analyze results, and iterate on models for state-of-the-art performance.
• Collaborate with research scientists and engineers to translate breakthroughs into production-ready code.
• Develop and maintain scalable deep learning training and inference pipelines.
• Stay current with the latest advancements in deep learning research and methodologies.

Connaissances

Deep learning

TensorFlow

PyTorch

Python

Research to production

Formation

Master's or PhD in CS/EE

Outils

JAX

NumPy

SciPy

Description du poste

Placements24 is seeking a Senior Deep Learning Engineer to join their fully remote team and drive breakthroughs in AI. You will design, implement, and optimize deep learning models for diverse applications, collaborating with research scientists and engineers across time zones.

The role emphasizes research, development, and scalable training/inference pipelines, with a focus on state-of-the-art results and production-ready code.