Job Description
Ovii's Interpretation of the Role
Senior Data Scientist driving LLM fine‑tuning and prompt engineering for a RegTech SaaS platform. Build pipelines, preprocess massive text corpora, and collaborate with backend and DevOps to ship AI‑powered compliance solutions.
Role Snapshot
- LLM fine‑tuning for chatbots & QA
- Prompt engineering and evaluation
- Large‑scale text data preprocessing
- Model performance analysis
- Collaboration with backend & DevOps
- Stay current on LLM research
Must-Have Requirements
- Strong understanding of NLP techniques
- 4-6 years experience as a Data Scientist
- Hands‑on prompt engineering
- Experience with deep learning frameworks (TensorFlow or PyTorch)
- Experience with large text datasets
- Excellent communication and collaboration skills
- Data Science
- NLP
Nice-to-Have Signals
- Experience with cloud platforms (AWS, GCP, Azure)
- Cloud platforms
Work Setup
- Location: Bangalore, India
- Work mode: ONSITE
- Employment type: Full-Time
Not Specified in JD
- Visa sponsorship
- Salary range
- Remote eligibility
- Education requirement
- Certifications
- Relocation
- Travel
- Security clearance
- Coding test
What You'll Likely Work On
- Fine‑tune open‑source LLMs for chatbots, question‑answering and recommendation use‑cases
- Pre‑process and clean large text / instruction datasets for model training
- Design and tweak prompts for different application contexts
- Experiment with various LLM architectures and training strategies
- Evaluate model performance, identify improvement areas, and iterate
- Integrate LLMs with the product stack alongside backend and DevOps teams
- Build inference pipelines to productionize multi‑tenant SaaS LLM services
- Stay up‑to‑date with the latest LLM research and contribute to product requirements
Good Fit If You Have
- Hands‑on experience with NLP techniques
- Proven track record of prompt engineering
- Experience handling large text corpora
- Familiarity with cloud platforms is a plus
- Strong communication and collaboration abilities
Skills
- Natural Language Processing (NLP)
- Prompt engineering
- Deep learning frameworks (TensorFlow, PyTorch)
- Large text dataset handling
- Python programming
- Cloud platforms (AWS, GCP, Azure)
- Model evaluation & metrics
- Collaboration & communication