Senior Applied Scientist

The Senior Applied Scientist role at the company involves developing advanced AI algorithms and models, focusing on deep learning and generative AI. This position provides a unique opportunity to work closely with product development teams and apply emerging technologies across diverse applications. Candidates should have a Master's or Ph.D. in a relevant field and at least 8 years of experience.

Responsibilities

• Engage in the design, analysis, and optimization of foundational and applied research to enhance AI algorithms and model capabilities.
• Create and optimize cutting-edge AI algorithms and deep learning models for various applications, including computer vision and natural language processing.
• Collaborate with researchers and engineers across teams for the continual improvement of AI algorithms, ensuring efficiency, reliability, and scalability.
• Integrate new algorithms and models into product offerings and conduct proof of concepts as per client needs.
• Propose scenarios where AI techniques could improve the customer’s business.
• Provide pre-sales and post-sales technical support to the business development team.

Qualifications

• M.Sc. or Ph.D. degree in computer science, engineering, or AI-related field.
• Minimum of 8 years of experience in developing AI algorithms for various modalities.
• Hands-on expertise designing and implementing GenAI solutions on Azure.
• Knowledge of Agentic AI designs and protocols (MCP, A2A, agentic orchestration).
• Hands-on experience with Python for prototyping and implementing GenAI solutions.
• Expertise in optimizing advanced RAG architectures and designing information retrieval systems.
• Azure Certifications (AI-900, AI-102, DP-100, AZ-305).

What working at the company offers

• Culture: An open, diverse, and inclusive environment focusing on groundbreaking innovations.
• Career: Outstanding learning, development & growth opportunities via structured training programs.
• Work-Life: A hybrid work policy to balance office and home life.
• Rewards: A competitive remuneration package with various perks including healthcare and education support.