Job Description
Designation: Senior AI/ML Engineer
Location: Gurugram
Industry: AI/ML Product based
About the Role
We are looking for a Senior AI/ML Engineer to lead the design and delivery of scalable, production-ready AI systems. This role combines deep hands-on engineering with technical leadership, owning the full lifecycle of machine learning solutions—from experimentation to deployment at scale. You will play a key role in shaping our AI strategy, building robust ML infrastructure, and delivering high-impact AI products in close collaboration with cross-functional teams.
Key Responsibilities
Architect, build, and deploy end-to-end machine learning pipelines and production-grade AI systems
Lead development of advanced ML models including LLMs, transformers, and deep learning architectures
Design and optimize Generative AI solutions such as RAG pipelines, prompt engineering, fine-tuning, and agent-based systems
Partner with data scientists, software engineers, and product teams to productionize ML solutions and integrate AI into core products
Define and implement MLOps best practices including CI/CD, experiment tracking, model monitoring, and governance
Drive technical design reviews and contribute to long-term AI infrastructure and platform decisions
Mentor junior engineers and raise engineering standards across the AI/ML team
Analyze large-scale datasets to improve model performance and reliability
Stay current with emerging AI technologies and evaluate their applicability to business needs
Communicate technical insights, trade-offs, and recommendations clearly to stakeholders and leadership
Required Qualifications
Bachelor’s degree in Computer Science, Machine Learning, Data Science, Mathematics, or a related field
7+ years of software engineering experience, with 4+ years focused on AI/ML or data science
Strong proficiency in Python and hands-on experience with PyTorch, TensorFlow, scikit-learn, and transformer-based frameworks
Experience working with proprietary LLMs (OpenAI GPT-4o / GPT-5, Claude, Gemini) and open-source models (Qwen, LLaMA, Mistral, DeepSeek), including fine-tuning and deployment
Proven experience deploying and maintaining ML systems in production at scale
Solid understanding of ML fundamentals including supervised/unsupervised learning, deep learning, NLP, and computer vision
Experience with cloud platforms such as AWS, GCP, or Azure and their ML services (SageMaker, Vertex AI, Azure ML)
Strong grasp of MLOps concepts: model versioning, monitoring, reproducibility, and experiment tracking
Excellent software engineering fundamentals: Git, testing, debugging, and deployment
Strong problem-solving skills and the ability to communicate complex ideas clearly
Preferred Qualifications
Hands-on experience with Generative AI systems including RAG architectures, prompt engineering, and agent frameworks (LangChain, LangGraph, CrewAI)
Experience in domains such as conversational AI, computer vision, or large-scale NLP systems
Prior experience mentoring or leading engineers in technical projects
