Job Description

Classical AI/ML

Design and implement

supervised and unsupervised ML models

including:

Linear Regression, Logistic Regression

Decision Trees, Random Forest, XGBoost

Naive Bayes, K-Means, SVM, PCA, etc.

Preprocess and analyze structured/tabular datasets

Evaluate models using metrics like accuracy, precision, recall, ROC-AUC, and RMSE

Build

predictive models

, deploy them into production, and monitor performance

Collaborate with business teams to translate requirements into ML use cases

Generative AI (GenAI)

Build and fine-tune

LLMs

(e.g., GPT, LLaMA, PaLM) for summarisation, Q&A, document generation, etc.

Implement

prompt engineering

,

RAG pipelines

, and

vector database integrations

Use libraries like

Hugging Face Transformers, LangChain, and LlamaIndex

Develop APIs to expose GenAI models in real-time apps

Optimise model inference using quantisation, batching, etc.

Ensure safe, explainable, and bias-free output in alignment with AI ethics guidelines

Required Skills & Qualifications

3.5 Yrs Bachelor's or Master's in Computer Science, Data Science, Statistics, or related field

Strong programming skills in

Python

, with experience in

NumPy, Pandas, Scikit-learn

Proficiency in

classical ML algorithms

(regression, trees, naive Bayes, etc.)

Experience with

LLM frameworks

like OpenAI API, Hugging Face, and LangChain

Understanding of

transformer architecture

, NLP, embeddings, and tokenisation

Familiarity with

REST API development

using FastAPI/Flask

Exposure to

cloud platforms

(AWS/GCP/Azure) and

Docker/Kubernetes

Job Type: Full-time

Pay: ?500,000.00 - ?900,000.00 per year

Work Location: In person