Key Responsibilities
- Conduct cutting-edge research in machine learning and artificial intelligence to advance model capabilities and performance.
- Design, implement, and evaluate state-of-the-art deep learning algorithms using frameworks such as TensorFlow and PyTorch.
- Collaborate with engineering teams to translate research breakthroughs into scalable, production-ready solutions with measurable impact.
- Publish research findings in peer-reviewed venues and contribute to global AI/ML scholarly communities through conferences and open-source efforts.
- Monitor and integrate advancements from the research community to maintain technological innovation.
- Document methodologies, experiments, and insights for technical and non-technical stakeholders.
Requirements
- Domain expertise in finance, healthcare, engineering, or specialized fields to contribute to AI training and evaluation.
- Hands-on experience with deep learning frameworks including TensorFlow, PyTorch, or equivalent.
- Strong research acumen demonstrated through publications, technical reports, or open-source contributions.
- Ability to design and execute experiments, analyze results using statistical methods, and iterate toward reproducible outcomes.
- Clear communication skills to translate technical concepts for diverse audiences.