Tiger Analytics - Senior NLP Engineer

Description :

Were looking for a talented and driven senior NLP practitioner to contribute to solving complex problems for our clients. You will contribute to both internal product development and client-focused projects, with a preference for candidates who have experience in the pharma domain. In this role, you will work closely with senior leadership to create transformative AI solutions for our clients while building and optimizing GenAI applications.

As part of this role, you will :

- Lead the design, development, and deployment of GenAI solutions, addressing challenges like hallucinations, bias, and latency, while ensuring performance and reliability.

- Collaborate with external and internal stakeholders, particularly in the pharma space, to understand business needs and create AI-powered systems tailored to their requirements.

- Lead full-lifecycle AI project delivery, including ideation, model fine-tuning, deployment, and continuous monitoring to maintain high performance in production environments.

- Apply advanced fine-tuning techniques (LoRA, PEFT) to Large Language Models (LLMs) for specific business needs, particularly in the pharma sector.

- Develop scalable pipelines to deploy AI models, including handling error management, robust monitoring, and retraining strategies.

- Mentor and lead a team of data scientists and AI engineers, fostering a culture of innovation, collaboration, and technical excellence.

Who do we expect :

- 12-18 years of experience in Analytics space leading NLP and AI projects.

- Expertise in Large Language Models (LLMs), Generative AI, and advanced fine-tuning techniques (LoRA, PEFT).

- Hands-on experience in deploying, scaling, and optimizing AI solutions for real-world business applications, with a focus on pharma-related use cases.

- Knowledge of AI-powered automation and working with LLM Agents, leveraging open-source frameworks.

- Proficiency in backend development with Python (Django/Flask) and experience with API and microservices architecture.

- Hands-on experience in MLOps, CI/CD pipelines, and containerization tools like Docker and Kubernetes.

- Experience with cloud platforms (AWS, GCP, Azure) for large-scale AI deployments.

- Experience in life sciences/pharma or similar regulated industries will be an added advantage.