Senior AI/ML Engineer

Primary Responsibilities:

• Design, develop, and deploy scalable AI/ML models to solve complex business challenges
• Lead end-to-end ML workflows, including data preprocessing, model training, hyperparameter tuning, and deployment
• Apply classical machine learning techniques (e.g., boosting, ensemble methods) and modern deep learning frameworks (e.g., PyTorch, TensorFlow) to deliver innovative solutions
• Work with large datasets using tools such as PySpark, Databricks, Pandas, and Numpy to enable data-driven decision-making
• Develop and fine-tune Generative AI and large language models (LLMs) using tools like Hugging Face, LangChain, and similar frameworks
• Collaborate with cross-functional teams to integrate AI/ML solutions with existing systems and applications
• Leverage cloud platforms like Azure AI, Azure ML, Google Cloud Platform, and OpenAI to build and deploy AI/ML models at scale
• Utilize ML lifecycle management tools (e.g., MLflow) to track and monitor model performance
• Conduct thorough data analysis using SQL to derive actionable insights and optimize model performance
• Explore and implement conversational AI systems (e.g., Dialogflow, Vertex AI) to enhance user interactions
• Stay up-to-date with the latest advancements in AI/ML technologies and recommend their adoption where relevant

Required Qualifications:

• Bacherlor's or Master's in Computer Science, Data Science, Machine Learning, or a related field

• Skill/Experience

  :
• 5+ years overall hands-on AI/ML project development using Python programming
• 5+ years deep learning using PyTorch
• 5+ years classical machine learning (e.g., sklearn, boosting, NLP)
• 5+ years data analysis using SQL
• 2+ years working with large datasets using PySpark, Databricks, Pandas, Numpy, etc.
• 2+ years experience with Transformers, Hugging Face, LLMs, Generative AI, LangChain
• 2+ years proficiency with Azure AI, Azure ML, OpenAI
• 2+ years ML model deployment (e.g., MLflow, Databricks, Azure)
• 1+ years healthcare domain and system knowledge
• 1+ years familiarity with Google Cloud Platform (e.g., Dialogflow, Vertex AI)
• Experience in the healthcare domain, including working with clinical or patient datasets
• Hands-on experience with Generative AI applications and building conversational agents
• Solid understanding of data engineering principles, including ETL pipelines and data workflows
• Proven ability to handle unstructured datasets, such as text, images, and audio
• Proven excellent problem-solving and critical-thinking skills
• Solid communication skills and the ability to collaborate with cross-functional stakeholders
• AI Scientist
• Design and develop foundational AI models and core components that power the organization's AI ecosystem, enabling scalable, reusable intelligence across products and services.
• Optimize infrastructure including model architecture, training pipelines, and deployment framework to ensure high performance and reliability
• Collaborate with research, engineering, and product teams to translate cutting-edge AI advancements into production-ready capabilities.
• Upload ethical AI principals by embedding fairness, transparency, and accountability throughout the model developmental life cycle.