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 solutionsfrom 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
