Consultant - Data Science

4 days ago

Bengaluru, Karnataka, India Trinity Life Sciences Full time
Job Description

DescriptionDescription

Job Title: GenAI Application Engineer (Consultant)

Location: Bangalore / Chennai / NCR (Hybrid)

Experience: 3.5 to 5.5 years

Employment Type: Full-time

Job Objective:

We are seeking a highly skilled and motivated GenAI Application Engineer with a strong foundation in traditional Machine Learning (ML) and hands-on experience in Generative AI (GenAI). The ideal candidate will contribute to the design, development, and deployment of AI-driven solutions across business use cases.

Key Responsibilities:

- Design and implement ML models including regression, classification, clustering, and optimization algorithms.
- Build and deploy GenAI applications using LLMs for tasks such as summarization, sentiment analysis, and content generation.
- Collaborate with cross-functional teams to identify opportunities for AI integration into business processes.
- Conduct research on emerging GenAI technologies and frameworks (e.g., LangChain, LlamaIndex).
- Fine-tune and optimize models for performance, scalability, and accuracy.
- Develop and maintain robust data pipelines and workflows.
- Stay updated with the latest advancements in AI, ML, and NLP.

Required Skills:

- Strong programming skills in Python.
- Solid understanding of traditional ML models and statistical techniques.
- Proficiency in working with GenAI tools and technologies such as LLMs, Retrieval-Augmented Generation (RAG), OpenAI APIs, LangChain, Streamlit, and vector databases.
- Hands-on experience with LLMs and GenAI tools (e.g., OpenAI, HuggingFace).
- Familiarity with prompt engineering and LLM fine-tuning.
- Exposure to cloud platforms (Azure preferred).

Qualifications

Preferred Qualifications:

- Masters degree in Computer Science, Data Science, Engineering, or related field.
- Experience in the life sciences or healthcare domain is a plus.
- Strong communication and stakeholder management skills.

Ability to work in a fast-paced, collaborative environment.

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