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AI/ML Engineer – Data Science & Data Engineering
AI/ML Engineer – Data Science & Data Engineering

AI/ML Engineer – Data Science & Data Engineering at TopGrep Tech Private Limited · Bengaluru (Bangalore) · 1 - 3 years · ₹3.5L - ₹4.5L / yr · Bootstrapped · Posted 7 Aug 2026

TopGrep Tech Private Limited's logo

AI/ML Engineer – Data Science & Data Engineering

Arka Mukherjee's profile picture
Posted by Arka Mukherjee
1 - 3 yrs
₹3.5L - ₹4.5L / yr
Bengaluru (Bangalore)
Skills
skill iconPython
skill iconKubernetes
skill iconDocker
TensorFlow
PySpark
PyCharm
Data engineering
skill iconData Science
Weaviate
Scikit-Learn
NumPy
pandas
Large Language Models (LLM)
LLM Evaluation Frameworks
Generative AI
Huggingface
n8n
SQL
LangChain
Pinecone
Vector database
LlamaIndex
Retrieval Augmented Generation (RAG)
ChromaDB
Artificial Intelligence (AI)
skill iconMachine Learning (ML)
skill iconDeep Learning

Key Responsibilities  

  • Design, build, and optimize scalable data pipelines for AI/ML applications.
  • Develop, train, evaluate, and deploy Machine Learning and Deep Learning models.
  • Build production-ready LLM applications using Retrieval-Augmented Generation (RAG), prompt engineering, and vector databases.
  • Fine-tune open-source and foundation models using domain-specific datasets.
  • Develop and maintain end-to-end MLOps pipelines for model deployment, monitoring, and lifecycle management.
  • Perform data preprocessing, feature engineering, exploratory data analysis (EDA), and model evaluation.
  • Develop APIs and AI services for production deployment.
  • Collaborate with cross-functional teams to deliver scalable AI-driven solutions.
  • Monitor model performance, troubleshoot production issues, and maintain technical documentation.


Required Skills  

Mandatory  

  • 1–3 years of experience in Data Science, Data Engineering, or AI/ML development.
  • Strong programming skills in Python and SQL.
  • Hands-on experience with Machine Learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
  • Experience building LLM-powered applications using RAG, Prompt Engineering, and Embeddings.
  • Hands-on experience with LangChain, LlamaIndex, CrewAI, or n8n for LLM orchestration and AI workflow automation.
  • Experience in LLM fine-tuning and working with Hugging Face models.
  • Knowledge of MLOps concepts including model deployment, monitoring, versioning, and CI/CD.
  • Experience with Git, REST APIs, Linux environments, and data processing libraries.


Preferred  

  • Experience with vector databases such as Pinecone, Chroma, Milvus, or Weaviate.
  • Familiarity with Docker, Kubernetes, and MLflow.
  • Exposure to Apache Spark or Airflow for data engineering workflows.
  • Experience with cloud platforms (AWS, Azure, or GCP).


Primary Technology Stack  

  • Languages & Data Processing: Python, SQL, Pandas, NumPy, Apache Spark
  • AI & Machine Learning: PyTorch, TensorFlow, Scikit-learn
  • Application Frameworks: LangChain, LlamaIndex, CrewAI, n8n
  • Core Methodologies: Retrieval-Augmented Generation (RAG), Model Fine-Tuning, Prompt Engineering, Embeddings
  • Models & Infrastructure: OpenAI APIs, Hugging Face Ecosystem, Embedding Models
  • Vector Databases: Pinecone, Chroma, Milvus, Weaviate
  • Databases: PostgreSQL, MongoDB
  • MLOps & DevOps: Docker, Kubernetes, MLflow, CI/CD, Git
  • Cloud Platforms: AWS, Azure, GCP


Experience: 1–3 Years

Domain: Data Science | Data Engineering | Machine Learning | Generative AI | MLOps

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About TopGrep Tech Private Limited

Founded :
2022
Type :
Product
Size :
0-20
Stage :
Bootstrapped

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What You Bring

  • Strong problem-solving and analytical skills.
  • Ability to translate business requirements into practical AI/ML solutions.
  • Strong software engineering and debugging capabilities.
  • Ability to work independently as well as collaboratively in a cross-functional environment.
  • Good communication skills with the ability to explain complex AI concepts to technical and non-technical stakeholders.

Keywords

AI Engineer | ML Engineer | Machine Learning | Generative AI | LLM | Python | NLP | Deep Learning | RAG | Prompt Engineering | AI Agents | Azure OpenAI | AWS Bedrock | MLOps | TensorFlow | PyTorch | Scikit-learn | Vector Database | Cloud AI

 

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Artificial Intelligence (AI)
skill iconMachine Learning (ML)
Natural Language Processing (NLP)

Roles & Responsibilities

  • Design and develop intelligent AI-based applications using advanced NLP and LLM techniques to solve real-world business challenges in financial services.
  • Build and optimize Retrieval-Augmented Generation (RAG) pipelines leveraging structured and unstructured financial data.
  • Integrate and orchestrate LLMs/SLMs for question-answering, summarization, semantic search, and document understanding.
  • Develop and maintain RESTful APIs (sync and async) to serve NLP models and chatbot interfaces using frameworks like FastAPI, Flask, etc.
  • Should have knowledge of advanced prompting techniques.
  • Implement semantic search, hybrid search, and text retrieval systems using Elasticsearch and vector databases (e.g., FAISS, Pinecone, Weaviate).
  • Perform NLP tasks such as entity recognition, text classification, intent detection, embedding generation, and sentiment analysis where required.
  • Monitor and fine-tune LLM/SLM performance with real-world user data to improve relevance, latency, and accuracy.
  • Exposure to LLMOps tools for monitoring, evaluation, and versioning of AI models in production.
  • Build, train, and evaluate deep learning models for NLP tasks including classification, NER, summarization, and embedding generation.
  • Develop traditional machine learning models (e.g., regression, decision trees, clustering) for structured data analysis and prediction tasks.
  • Interact with cross-functional teams to understand system issues and follow up with respective teams to get them fixed.
  • Understand and identify areas of improvement across businesses and participate in solution identification and implementation.
  • Should be able to work as an Individual Contributor on new and existing projects.
  • Positive and problem-solving attitude, must work as an independent contributor.

Ideal Candidate

1.Strong Data Scientist / AI Engineer / Generative AI Engineer profile.

2.Mandatory (Experience 1) - Must have 3+ years of hands-on experience in Data Science, Artificial Intelligence, Machine Learning, Deep Learning, NLP, or Generative AI application development.

3.Mandatory (Experience 2) - Must have strong hands-on experience in Python programming, backend development, API development, and production-grade application support

4.Mandatory (Experience 3) - Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, or Scikit-learn.

5.Mandatory (Experience 4) - Must have hands-on experience in NLP use cases such as text classification, sentiment analysis, entity recognition (NER), semantic search, embeddings, or document understanding.

6.Mandatory (Experience 5) - Must have experience working with Large Language Models (LLMs) such as GPT, LLaMA, Mistral, Phi, Claude, Gemini, or similar models

.7.Mandatory (Experience 6) - Must have hands-on experience building or implementing Retrieval Augmented Generation (RAG) solutions, vector search, semantic search, or knowledge-based AI applications.

8.Mandatory (Experience 7) - Must have experience with Prompt Engineering and Generative AI frameworks such as LangChain, LangGraph, AI Agents, Azure OpenAI, or similar technologies.

9.Mandatory (Experience 8) - Must have experience developing, consuming, or integrating APIs using Python frameworks such as FastAPI, Flask, or similar technologies.

10.Mandatory (CTC) - The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

11.Preferred (Experience 1) - Experience with LLMOps/MLOps tools for monitoring, evaluation, experimentation, and versioning of AI models.

12.Preferred (Experience 2) - Exposure to Azure OpenAI, Azure Kubernetes Service (AKS), Kubernetes, cloud-native AI deployments, or distributed systems.

13.Preferred (Experience 3) - Experience working with PostgreSQL, MongoDB, Redis, Kafka, or large-scale data platforms.

14.Preferred (Experience 4) - Familiarity with Docker, Kubernetes, cloud platforms, and scalable deployment architecture.

15.Preferred (Company) - Candidates from AI-first startups, product companies, SaaS organizations, fintech, or data-driven technology companies.

16.Mandatory ( Age ) - Candidate Should be Below 28 Years.

17.Mandatory ( Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered.

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Shubham Vishwakarma

Full Stack Developer - Averlon
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