Senior AI Engineer / Senior Machine Learning Specialist

"> About the Role

• Lead the design, development, deployment, and optimization of AI/ML solutions for enterprise-scale applications.
• Architect scalable Machine Learning pipelines and production-ready AI systems.
• Build, train, fine-tune, evaluate, and deploy advanced Machine Learning and Deep Learning models.
• Drive initiatives in Generative AI, Large Language Models (LLMs), NLP, Computer Vision, and predictive analytics.
• Design and implement end-to-end MLOps pipelines for model deployment, monitoring, versioning, and continuous improvement.
• Collaborate with product owners, business stakeholders, engineering teams, and data scientists to translate business requirements into AI-driven solutions.
• Mentor and provide technical guidance to junior AI/ML engineers and data scientists.
• Perform advanced data analysis, feature engineering, model optimization, and performance tuning.
• Ensure AI models are scalable, secure, reliable, and aligned with organizational standards.
• Stay updated with emerging AI technologies, research, and industry best practices, driving innovation across projects.

• Python (Mandatory)
• R
• Java

• TensorFlow
• PyTorch
• Keras
• Scikit-learn
• OpenCV
• Hugging Face Transformers
• LangChain / LlamaIndex (Preferred)

• Pandas
• NumPy
• SQL
• Apache Spark
• Data Engineering concepts

• AWS AI/ML Services
• Microsoft Azure AI Services
• Google Cloud Platform (Vertex AI)

• Git
• Docker
• Kubernetes
• MLflow
• CI/CD Pipelines
• Model Monitoring Deployment

• Machine Learning
• Deep Learning
• Generative AI
• Large Language Models (LLMs)
• Natural Language Processing (NLP)
• Computer Vision
• Recommendation Systems
• Model Deployment Optimization
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• AI Governance and Responsible AI

• 6 9+ years of experience in Artificial Intelligence, Machine Learning, or Data Science.
• Proven experience delivering end-to-end AI/ML solutions in production environments.
• Strong experience in designing scalable AI architectures and deploying enterprise-grade ML models.
• Experience working with cloud-native AI services and MLOps practices.
• Experience mentoring junior engineers and leading technical initiatives.
• Exposure to Agile development methodologies and cross-functional collaboration.
• Excellent analytical, problem-solving, and communication skills.

• Microsoft Certified: Azure AI Engineer Associate
• AWS Certified Machine Learning Specialty
• Google Professional Machine Learning Engineer
• TensorFlow Developer Certificate
• Databricks Machine Learning Professional (Preferred)

• Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.