Senior AI Engineer / Senior Machine Learning Specialist

Summary: Leads the design, development, and deployment of advanced AI and machine learning solutions, from concept to production. Mentors technical teams and drives AI initiatives using generative AI, NLP, and computer vision.

About the Role

We are looking for a highly skilled Senior AI Engineer / Senior Machine Learning Specialist to lead the design, development, and deployment of advanced AI and Machine Learning solutions. The ideal candidate will have extensive hands-on experience in building scalable AI systems, mentoring technical teams, and driving AI initiatives from concept to production. This role requires strong expertise in Generative AI, NLP, Computer Vision, MLOps, and cloud-based AI solutions while collaborating with cross-functional stakeholders to deliver business-driven outcomes.

Key Responsibilities

• 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.

Required Skills & Technology Stack

### Programming Languages

• Python (Mandatory)
• R
• Java

### AI/ML Frameworks & Libraries

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

### Data & Analytics

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

### Cloud Platforms

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

### DevOps & MLOps

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

### AI Expertise

• 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

Required Experience

• 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.

Preferred Certifications

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

Educational Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.