Senior 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.