Machine Learning Engineer

Paisabazaar; Gurugram District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Paisabazaar is seeking an AI Engineer with 2-6 years of software and AI experience to design, develop, and deploy AI/ML solutions, including Generative AI, LLMs, and RAG pipelines.

You will build production-ready AI services using Python, FastAPI, Docker, and Kubernetes, integrating LLMs with internal tools and APIs while optimizing performance, latency, and cost. Collaboration with product teams is essential.

Qualifications

• 2-6 years of experience in software development, backend engineering, AI/ML engineering, or a related field.
• Strong programming skills in Python.
• Hands-on experience with Generative AI and LLM-based applications.
• Experience with RAG, embeddings, vector databases, semantic search, and prompt engineering.
• Experience developing REST APIs using Python/FastAPI.
• Familiarity with OpenAI, Anthropic, Gemini, Llama, Qwen, or similar LLM platforms/models.
• Experience with Git, Docker, and software development best practices.
• Understanding of databases, APIs, and backend application development.
• Basic to good understanding of AWS, Azure, or GCP.
• Familiarity with LangChain, LlamaIndex, or equivalent AI frameworks.
• Understanding of AI/LLM evaluation, monitoring, and model optimization is a plus.
• Strong analytical, problem-solving, and communication skills.
• Ability to learn new AI technologies and apply them to real-world business problems.

Responsibilities

• Design, develop, test, and deploy AI/ML and Generative AI applications.
• Build and maintain RAG (Retrieval-Augmented Generation) pipelines using embeddings, vector databases, and semantic search.
• Integrate LLMs with internal tools, APIs, databases, and enterprise applications.
• Develop scalable and production-ready backend services using Python and FastAPI.
• Work with LLMs such as OpenAI, Anthropic, Gemini, Llama, Qwen, or other open-source models.
• Develop and optimize prompts, AI workflows, and model evaluation frameworks.
• Implement techniques to improve AI application accuracy, performance, latency, reliability, and cost efficiency.
• Work with vector databases and technologies for embeddings, similarity search, and semantic retrieval.
• Develop and integrate REST APIs and backend services.
• Containerize and deploy AI services using Docker and contribute to deployment on Kubernetes environments.
• Work with cloud platforms such as AWS, Azure, or GCP.
• Use AI frameworks such as LangChain, LlamaIndex, or similar frameworks.
• Collaborate with senior engineers, product managers, and cross-functional teams to translate business requirements into AI solutions.
• Participate in testing, debugging, monitoring, and production support of AI services.
• Stay updated with emerging Generative AI, LLM, and AI engineering technologies.

Skills

Python

AI/ML engineering

Generative AI

LLM-based applications

RAG pipelines

Embeddings

Semantic search

Prompt engineering

REST APIs

Backend development

Cloud technologies

Git

Docker

Kubernetes

LangChain

Education

B.Tech / B.E.

M.Tech

Tools

FastAPI

Docker

Kubernetes

Git

Python ecosystem

LLM platforms/tools

Job description

AI Engineer

Experience: 2-6 Years
Job Type: Full-Time

Job Description

We are looking for a talented AI Engineer with 2-6 years of software engineering experience to design, develop, and deploy AI/ML and Generative AI solutions. The ideal candidate will have hands‑on experience with Python, LLMs, RAG pipelines, APIs, vector databases, and cloud technologies, along with a strong interest in building scalable AI-powered applications.

You will work closely with product and engineering teams to develop production‑ready AI solutions, integrate LLMs with enterprise applications and internal tools, and continuously improve the performance, reliability, latency, and cost of AI services.

Key Responsibilities

• Design, develop, test, and deploy AI/ML and Generative AI applications.
• Build and maintain RAG (Retrieval-Augmented Generation) pipelines using embeddings, vector databases, and semantic search.
• Integrate LLMs with internal tools, APIs, databases, and enterprise applications.
• Develop scalable and production‑ready backend services using Python and FastAPI.
• Work with LLMs such as OpenAI, Anthropic, Gemini, Llama, Qwen, or other open‑source models.
• Develop and optimize prompts, AI workflows, and model evaluation frameworks.
• Implement techniques to improve AI application accuracy, performance, latency, reliability, and cost efficiency.
• Work with vector databases and technologies for embeddings, similarity search, and semantic retrieval.
• Develop and integrate REST APIs and backend services.
• Containerize and deploy AI services using Docker and contribute to deployment on Kubernetes environments.
• Work with cloud platforms such as AWS, Azure, or GCP.
• Use AI frameworks such as LangChain, LlamaIndex, or similar frameworks.
• Collaborate with senior engineers, product managers, and cross‑functional teams to translate business requirements into effective AI solutions.
• Participate in testing, debugging, monitoring, and production support of AI services.
• Stay updated with emerging Generative AI, LLM, and AI engineering technologies and evaluate their applicability to business problems.

Required Skills

• 2-6 years of experience in software development, backend engineering, AI/ML engineering, or a related field.
• Strong programming skills in Python.
• Hands‑on experience with Generative AI and LLM-based applications.
• Experience with RAG, embeddings, vector databases, semantic search, and prompt engineering.
• Experience developing REST APIs using Python/FastAPI.
• Familiarity with OpenAI, Anthropic, Gemini, Llama, Qwen, or similar LLM platforms/models.
• Experience with Git, Docker, and software development best practices.
• Understanding of databases, APIs, and backend application development.
• Basic to good understanding of AWS, Azure, or GCP.
• Familiarity with LangChain, LlamaIndex, or equivalent AI frameworks.
• Understanding of AI/LLM evaluation, monitoring, and model optimization is a plus.
• Strong analytical, problem‑solving, and communication skills.
• Ability to learn new AI technologies and apply them to real‑world business problems.

Good to Have

• Experience deploying AI applications in production.
• Experience with Kubernetes and cloud‑native architectures.
• Knowledge of LLM fine‑tuning, function calling/tool use, agents, or multimodal AI.
• Experience with AI observability, evaluation, and monitoring tools.
• Knowledge of CI/CD and MLOps practices.
• Experience working with enterprise applications and integrating AI into existing business workflows.

Education

• B.Tech / B.E. in Computer Science, Information Technology, Artificial Intelligence, Machine Learning, or a related engineering discipline.
• M.Tech in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related engineering discipline.
• Only B.Tech/B.E. or M.Tech candidates will be considered.