AI Researcher

Job Summary:

We are seeking a highly motivated and innovative AI Researcher to join our advanced technology team. The role involves conducting cutting-edge research in artificial intelligence and machine learning, developing novel algorithms, publishing findings, and contributing to real-world AI product implementations.

Key Responsibilities:

• Conduct original research in AI/ML domains such as deep learning, reinforcement learning, computer vision, NLP, generative models, or optimization.

• Design, prototype, and evaluate new algorithms and models to solve complex problems.

• Publish research findings in top-tier academic journals and present at leading AI conferences.

• Collaborate with engineering teams to transfer research into production-ready solutions.

• Stay current with the latest developments in AI, machine learning, and data science.

• Contribute to intellectual property development (e.g., patents, publications).

• Explore and benchmark emerging tools, frameworks, and techniques.

• Mentor junior researchers or interns and contribute to the team's research culture.

Requirements:

• Masters or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

• Strong foundation in mathematics and statistics (e.g., linear algebra, probability, optimization).

• Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX.

• Proven track record of research contributions (e.g., peer-reviewed papers, preprints, GitHub projects).

• Proficiency in Python and relevant ML libraries (e.g., NumPy, SciPy, Scikit-learn).

• Excellent analytical thinking, experimentation, and communication skills.

• Ability to work independently as well as in collaborative, interdisciplinary teams.

Preferred Qualifications:

• Experience with LLMs, diffusion models, or generative AI (e.g., GPT, BERT, Stable Diffusion).

• Familiarity with MLOps, model deployment, or large-scale experimentation.

• Participation in AI research competitions (e.g., Kaggle, NeurIPS, CVPR challenges).

• Knowledge of cloud platforms (e.g., AWS, GCP, Azure) for AI model training and deployment.