Starmark Software - Artificial Intelligence Engineer/Data Scientist - Generative AI (7-10 yrs)

Role Overview :

We are seeking an accomplished and visionary Data Scientist with minimum 5 Years of experience in Data Science and Machine learning, preferable experience around NLP, Generative AI, LLMs, MLOps, Optimization techniques and AI solution Architecture to lead our AI team and drive the strategic direction of AI initiatives.

In this role you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise and leadership skills.

The ideal candidate should have a proven track record in AI leadership, a deep understanding of AI technologies, and experience in designing and implementing cutting-edge AI models and systems.

Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Minimum 5 Years of experience in Data Science and Machine learning.

Excellent leadership skills with at least 2-3 years of people management OR technical architecture experience.

Responsibilities :

Your technical responsibilities :

- Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions.

- Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance.

- Drive the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI.

- Collaborate with stakeholders to identify business opportunities, define AI project goals, and prioritize initiatives based on strategic objectives.

- Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges.

- Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases.

- Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment.

- Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs.

- Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly.

- Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency.

- Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases.