Senior AI ML Engineer

Job Summary
We are looking for a highly skilled Senior AI/ML Engineer to lead the design, development, deployment, and optimization of AI/ML solutions across diverse enterprise use cases. The ideal candidate should possess strong expertise in machine learning, deep learning, generative AI, LLMs, and MLOps, with the ability to translate business problems into scalable AI solutions.
This role involves mentoring junior engineers, driving technical decisions, and collaborating closely with product, engineering, and business teams to deliver production-grade AI systems.

Key Responsibilities

• Design and develop end-to-end AI/ML solutions for enterprise applications across NLP, Computer Vision, Predictive Analytics, Recommendation Systems, Generative AI, and Conversational AI domains.
• Build, fine-tune, and optimize machine learning and deep learning models for performance, scalability, and reliability.
• Develop and deploy LLM-powered applications, AI agents, RAG systems, and workflow automation solutions.
• Design data pipelines, feature engineering frameworks, and model training workflows for large-scale datasets.
• Lead model evaluation, experimentation, hyperparameter tuning, and performance optimization initiatives.
• Implement MLOps best practices for model deployment, monitoring, versioning, and continuous improvement.
• Collaborate with cross-functional teams to understand business requirements and translate them into AI-driven solutions.
• Mentor junior engineers and provide technical guidance on AI architecture, coding standards, and best practices.
• Drive research and innovation by evaluating emerging AI technologies, frameworks, and methodologies.
• Ensure production systems meet reliability, scalability, security, and compliance requirements.
  Required Skills
• Strong foundation in Machine Learning, Deep Learning, Statistics, and Data Science.
• Hands-on experience with Python and AI/ML frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, and LangChain.
• Experience building and deploying machine learning models in production environments.
• Expertise in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI Agent frameworks.
• Experience with data processing frameworks and databases such as Pandas, Spark, SQL, Vector Databases, and NoSQL systems.
• Strong understanding of model optimization, evaluation metrics, and performance tuning.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Familiarity with containerization and deployment technologies including Docker and Kubernetes.
• Knowledge of MLOps tools and CI/CD practices for AI systems.
• Strong problem-solving, debugging, and analytical skills.

Preferred Skills

• Experience in one or more specialized domains such as NLP, Computer Vision, Speech AI, Time-Series Forecasting, or Recommender Systems.
• Experience building enterprise-grade AI platforms and multi-agent systems.
• Knowledge of distributed training, model quantization, and inference optimization.
• Exposure to edge AI deployment and real-time AI systems.
• Contributions to research publications, patents, or open-source AI projects.
• Experience leading technical teams and mentoring engineers.