Primary Skills : Agentic AI, Gen AI, LLMs, NLP, AI / ML, Data Science, AWS / GCP, API Deployment for SAAS, MLOps practices for CI / CD
Roles & Responsibilities :
- Develop Agents, Gen AI Solutions, Custom data models and algorithms to apply to data sets.
- Developing and implementing advanced machine learning models to address complex problems.
- Clearly communicate findings and recommendations, data-driven insights to PMs and executives.
- Lead and mentor a team of data scientists, providing guidance on best practices and technical expertise.
- Collaborate with cross-functional teams to define data-driven strategies and integrate Agentic / AI / ML / Gen AI solutions into products.
- Continuously evaluate and improve the performance of existing models and algorithms.
- Stay updated with the latest advancements in Agentic AI / Gen AI / AI / ML and propose innovative solutions to enhance the company's capabilities.
Requirements :
Bachelor's / Master's degree in Computer Science, Engineering, or a related technical field with a minimum of 7-8 years' experience.Minimum of 2 years of experience in leading a team of junior Data Scientists.Should have been involved in end-to-end delivery of the scalable, optimized and enterprise AI solutions.Experience in performing prompt engineering and fine-tuning of the AI / ML, GenAI, LLM models & building AgentsPractical hands-on fine-tuning / transfer learning / optimisation of the Transformer architecture-based Deep Learning models.Experience in Agentic AI, Gen AI, LLM, NLP tools such as Word2Vec, TextBlob, NLTK, SpaCy, Gensim, CoreNLP, BERT, GloVe etc.Experience in AWS / GCP cloud and deploying the APIs using the latest frameworks like FastAPI / gRPC etc.Experience in Docker for deploying the containers.Deployment of the ML models on the Kubernetes clustersExperience in NoSQL / SQL databases.Good programming skills in Python.Domain knowledge in Online Reputation management or experience in a product-based company (added advantage).Expertise in delivering end-to-end AI solutions covering multiple technologies & tools to multiple business problems.Strong knowledge of statistical methods and experimental design.Experience with MLOps practices for CI / CD in machine learning.Strong project management skills, with the ability to manage multiple projects simultaneously.Excellent communication and presentation skills, with the ability to explain complex technical concepts to non-technical stakeholders(ref : hirist.tech)