Senior AI/ML Engineer

We are seeking an experienced and highly skilled Senior AI/ML Engineer with 12+ years of overall IT experience and extensive expertise in designing, developing, deploying, and scaling enterprise-grade Artificial Intelligence and Machine Learning solutions. The ideal candidate will have a strong background in machine learning, deep learning, generative AI, MLOps, cloud platforms, and large-scale data processing. This role requires technical leadership, architectural decision-making, mentoring capabilities, and the ability to collaborate with cross-functional teams to deliver innovative AI-driven products and solutions. Key Responsibilities Design, develop, and deploy scalable AI/ML solutions for complex business challenges. Lead end-to-end machine learning lifecycle activities including data preparation, feature engineering, model development, evaluation, deployment, monitoring, and optimization. Architect and implement advanced machine learning, deep learning, NLP, computer vision, recommendation systems, and predictive analytics solutions. Develop and optimize Generative AI applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, and AI agents. Build and maintain robust MLOps pipelines for automated model training, deployment, versioning, monitoring, and governance. Collaborate with data scientists, data engineers, software engineers, product managers, and business stakeholders to translate business requirements into AI solutions. Drive AI architecture discussions and establish best practices for model development, deployment, scalability, and security. Evaluate emerging AI/ML technologies, frameworks, and industry trends to recommend innovative solutions. Develop APIs and microservices for model serving and AI application integration. Ensure model reliability, explainability, fairness, compliance, and responsible AI practices. Optimize model performance, inference latency, and resource utilization in production environments. Lead code reviews, technical design reviews, and architecture governance activities. Mentor junior engineers and provide technical leadership across AI/ML initiatives. Define standards and best practices for machine learning engineering, experimentation, and model governance. Work closely with DevOps and cloud teams to implement scalable AI infrastructure. Support production deployments, troubleshooting, monitoring, and continuous improvement initiatives. Required Qualifications Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, Statistics, or a related field. 12+ years of overall software engineering experience with at least 6+ years focused on AI/ML engineering. Strong expertise in Machine Learning, Deep Learning, Statistical Modeling, and Predictive Analytics. Hands-on experience with Python and AI/ML development ecosystems. Extensive experience with TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, and related frameworks. Strong knowledge of NLP, Transformers, LLMs, Generative AI, and foundation models. Experience building RAG architectures, vector search solutions, AI copilots, and conversational AI systems. Expertise in prompt engineering, fine-tuning, model evaluation, and LLM optimization techniques. Experience working with vector databases such as Pinecone, Weaviate, Chroma, or FAISS. Strong understanding of distributed data processing frameworks including Spark and Databricks. Experience with cloud platforms such as AWS, Azure, and Google Cloud Platform. Hands-on experience with containerization and orchestration technologies including Docker and Kubernetes. Strong knowledge of MLOps tools such as MLflow, Kubeflow, Airflow, SageMaker, Azure ML, or Vertex AI. Experience building REST APIs using FastAPI, Flask, or similar frameworks. Proficiency with SQL and NoSQL databases. Experience implementing CI/CD pipelines for AI/ML applications. Strong understanding of software engineering principles, design patterns, and scalable system architecture. Experience working in Agile/Scrum environments. Preferred Skills Experience with multi-agent AI systems and autonomous AI workflows. Knowledge of Graph RAG, Knowledge Graphs, and semantic search architectures. Exposure to reinforcement learning and advanced deep learning techniques. Experience with AI governance, model explainability, and responsible AI frameworks. Familiarity with streaming platforms such as Kafka and real-time AI applications. Experience in healthcare, finance, retail, manufacturing, or enterprise AI domains. Relevant certifications in AWS, Azure, Google Cloud Platform, AI/ML, or Data Engineering. Key Competencies Technical Leadership and Solution Architecture Strategic Problem Solving Stakeholder Management Mentoring and Team Development Strong Communication and Presentation Skills Innovation Mindset and Continuous Learning Enterprise Solution Design Cross-functional Collaboration Ownership and Accountability