Sr. AI/ML Engineer

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

Job summary

Astroyogi is seeking an AI/ML engineer to design, develop, and deploy scalable AI/ML solutions for business and customer-facing applications. You will build agentic AI-based applications and integrate models using Generative AI, NLP, and ML techniques.

The role requires strong hands-on Python/SQL, experience with LLMs and AI APIs, and a track record of production-grade AI systems, including embeddings, vector search, and RAG components.

Qualifications

• 3 years of hands-on AI/ML engineering experience or related field.
• Strong Python and SQL programming skills.
• Solid understanding of ML, DL, NLP, and Generative AI.
• Practical experience with LLMs and AI APIs (OpenAI, Anthropic, Gemini, Hugging Face).
• Hands-on experience with RAG/agentic AI apps, embeddings, vector search, evaluation.

Responsibilities

• Design, develop, and deploy scalable AI/ML solutions for business apps.
• Build agentic AI and AI agent-based applications.

Skills

Python

SQL

ML

NLP

Generative AI

LLMs

RAG

Prompt engineering

AI agents

REST APIs

Cloud

Docker

CI/CD

Vector databases

Tools

Docker

CI/CD

Vector databases (Pinecone, Qdrant, Weaviate, Milvus)

Job description

• Design, develop, and deploy scalable AI/ML solutions for business and customer-facing applications.
• Build Agentic AI / AI agent based applications.
• Develop and integrate solutions using Generative AI, Large Language Models (LLMs), NLP, and Machine Learning.
• Build intelligent applications using RAG, embeddings, vector search, prompt engineering, tool/function calling, and AI agents.
• Research, evaluate, and select appropriate models, frameworks, and technologies based on business and technical requirements.
• Develop efficient data and ML pipelines for data preparation, experimentation, model evaluation, deployment, and monitoring.
• Integrate AI/ML models with existing products, APIs, databases, and backend systems.
• Evaluate model performance and continuously improve accuracy, relevance, latency, reliability, and cost efficiency.
• Implement appropriate AI evaluation, monitoring, logging, and guardrails for production systems.
• Work closely with Product, Engineering, Data, and Business teams to understand requirements and translate them into practical AI solutions.
• Take end-to-end ownership of AI/ML projects from proof of concept to production deployment and continuous improvement.
• Identify opportunities to apply AI/ML to improve products, processes, automation, and customer experiences.
• Contribute to technical architecture, code quality, documentation, and engineering best practices.
• Mentor and support junior engineers while contributing to a collaborative engineering environment.

Required Skills & Experience

• 3 years of professional hands on experience in AI/ML engineering or a related field.
• Strong hands-on programming experience with Python, SQL.
• Strong understanding of Machine Learning, Deep Learning, NLP, and Generative AI.
• Practical experience working with LLMs and AI APIs such as OpenAI, Anthropic, Gemini, Hugging Face, or equivalent technologies.
• Hands-on experience developing RAG / agentic AI based applications, including embeddings, retrieval, vector search, and evaluation.
• Strong understanding of prompt engineering, structured outputs, function/tool calling, and AI agents.
• Experience building and deploying production-grade AI/ML applications.
• Good understanding of REST APIs, databases, backend systems, and scalable application architecture.
• Experience with vector databases such as Pinecone, Qdrant, Weaviate, Milvus, pgvector, or equivalent.
• Familiarity with cloud platforms such as AWS, GCP, or Azure.
• Experience with Docker, CI/CD, deployment, monitoring, and production engineering practices.
• Good understanding of model evaluation, experimentation, and performance optimization.
• Strong analytical, problem-solving, and debugging skills.

What We Are Looking For

• Strong ownership and the ability to independently drive AI/ML projects.
• A practical approach to applying AI to real-world business problems.
• Strong combination of AI/ML expertise and software engineering fundamentals.
• Ability to take solutions from experimentation to stable, scalable production systems.
• Strong focus on quality, performance, scalability, security, and cost efficiency.
• Curiosity and willingness to stay updated with the rapidly evolving AI/ML ecosystem.
• Strong communication and collaboration skills.
• Ability to work effectively in a fast-paced and evolving technology environment.