Sr. AI/ML Engineer

Key Responsibilities
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.

Work arrangement
No