AI/ML Engineer

Scriptshub Technologies; Pune District; On-site; INR 600,000 - 1,000,000; Full time

Job summary

Scriptshub Technologies is seeking an AI/ML engineer to assist in developing, testing, and deploying ML models and AI-powered features. You will build data pipelines for both structured and unstructured data and integrate LLMs into application workflows using APIs and LangChain.

The role involves experimenting with ML algorithms for predictive modeling, building RAG pipelines with vector databases, and exposing model inferences through REST APIs with FastAPI or Flask.

Qualifications

• Solid understanding of core ML algorithms including regression, classification, clustering.
• Proficiency in Python and libraries NumPy, Pandas, Scikit-learn.
• Familiarity with at least one DL 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.
• Git for version control.
• Basic understanding of data structures and algorithms.

Responsibilities

• Assist in developing, testing, and deploying ML models and AI features.
• Build and maintain data preprocessing pipelines for structured/unstructured data.
• Experiment with ML algorithms for predictive modeling, classification, clustering.
• Integrate LLMs like GPT or Claude into workflows via APIs/frameworks.
• Support RAG pipelines using vector databases (ChromaDB/FAISS).
• Expose model inference via REST APIs using FastAPI or Flask.
• Collaborate with cross-functional teams to translate requirements.
• Perform model evaluation, benchmarking, and iterative optimization.
• Write clean, documented, version-controlled code using Git.
• Stay current with AI/ML advancements, especially LLM/GenAI.

Skills

ML algorithms

Python

Python libraries

DL framework

LLMs basics

API development

SQL

Git basics

DS&A basics

Education

Bachelor's degree in CS/IT/DS/AI

Certifications in AI/ML (advantage)

Tools

FastAPI

Flask

LangChain

ChromaDB

FAISS

Docker

Jupyter

Job description

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 environment.
• Collaborative team player who takes ownership of assigned work.