Role & responsibilities

- Assist in developing, testing, and deploying machine learning models and AI-powered features.

- Build and maintain data preprocessing pipelines for structured and unstructured datasets.

- Implement and experiment with ML algorithms for predictive modeling, classification, and clustering tasks.

- Assist in integrating Large Language Models (LLMs) such as OpenAI GPT or Anthropic Claude into application workflows using APIs and frameworks like LangChain.

- Support development of RAG (Retrieval-Augmented Generation) pipelines using vector databases such as ChromaDB or FAISS.

- Expose ML model inference through lightweight REST APIs using FastAPI or Flask.

- Collaborate with cross-functional teams (frontend, backend, data engineering) to translate business requirements into AI-based solutions.

- Perform model evaluation, benchmarking, and iterative optimization.

- Write clean, documented, version-controlled code using Git.

- Stay current with advancements in AI/ML, particularly in the LLM and GenAI space.

Required Skills:

- Solid understanding of core ML algorithms Regression, Classification, Clustering, Dimensionality Reduction.

- Proficiency in Python and key libraries: NumPy, Pandas, Scikit-learn.

- Familiarity with at least one Deep Learning framework TensorFlow or PyTorch.

- Basic understanding of LLMs and prompt engineering concepts.





- Exposure to API development using FastAPI or Flask.

- Working knowledge of SQL for data querying and manipulation.

- Familiarity with Git for version control.

- Basic understanding of data structures and algorithms

Good to Have:

- Hands-on exposure to LangChain or similar LLM orchestration frameworks.

- Experience with vector databases (ChromaDB, FAISS, Pinecone).

- Familiarity with cloud platforms AWS, Azure, or GCP (even at a free-tier/academic level).

- Basic understanding of MLOps concepts experiment tracking (MLflow), model versioning, or containerization (Docker).

- Exposure to Jupyter Notebooks and experiment documentation practices

Educational Qualification:

- Bachelor's degree in Computer Science, IT, Data Science, Artificial Intelligence, or a related field.

- Relevant certifications (e.g., DeepLearning.AI, Google ML Crash Course, Hugging Face NLP Course) or academic AI/ML projects are a strong advantage.

- Candidates with strong GitHub portfolios or Kaggle competition experience will be preferred.

Soft Skills:

- Clear written and verbal communication essential for working with international clients.

- Strong curiosity and a self-driven approach to learning.

- Comfortable working iteratively in a fast-paced, feedback-heavy setting.

- Collaborative team player who takes ownership of assigned work.

📌 AI/ML Engineer (Pune)
🏢 ScriptsHub Technologies
📍 Pune