Artificial Intelligence Engineer

Designation: Senior AI/ML EngineerLocation: GurugramWork Model: 5 days (WFO)Budget: 50 LPAIndustry: AI/ML Product basedAbout the RoleWe 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 leadershipRequired 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 clearlyPreferred 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

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