AI/ML Subject Matter Expert

Responsibilities

• Responsible for developing and implementing AI/ML solutions to solve complex problems and enhance business operations.
• Define direction of mission-critical solutions using best-fit AI/ML algorithms and technologies
• Work closely with cross-functional teams to design, develop, and deploy AI models and algorithms that enable data-driven decision making.
• Conduct statistical analyses using ML techniques for customer-focused solutions
• Collaborate with cross-functional teams to deliver world-class solutions for large-scale data processing
• Guide clients in navigating ML algorithms, tools, and frameworks
• Design, develop, and deploy AI models for data-driven decision making and business innovation
• Create intelligent systems that automate processes, improve efficiency, and drive business innovation, leveraging their expertise in AL/ML, deep learning, and data analysis.
• Create, train, and maintain intelligent systems to automate processes and improve efficiency
• Report on industry trends and recommend solutions for AI/ML integration
• Design and build ML models solving real-world business problems
• Make informed ML infrastructure decisions based on modeling techniques and issues
• Write and test application code, develop ML models, and automate tests and deployment
• Retrain, maintain, and monitor production models
• Leverage cloud-based architectures to deliver optimized ML models at scale
• Construct optimized data pipelines for ML models
• Implement CI/CD best practices for ML model and application code deployment
• Ensure code security, model governance, and adherence to Responsible and Explainable AI practices
• Regularly recommend and report on industry trends and solutions to meet evolving client needs regarding techniques, tools and technologies for AI/ML integration.
• Requirements:
• Master's degree or Bachelor's of science with 5+ years of industry experience in Computer Science, Software Engineering, Data Science, Statistics, or related STEM field.
• 5+ years of experience in AI, data science, ML engineering, or related fields
• 4+ years of experience with modern cloud computing technologies (AWS, Databricks, Microsoft Azure or GCP)
• Experience in fine-tuning LLMs for custom datasets and/or using RAG to augment LLM applications.
• Knowledge of multiple ways of tackling AI/ML problems and demonstrated ability to make good initial choices to make systems that perform well more quickly
• Experience using Generative AI tools to help in software programming and testing (e.g. VS-Code or GitHub with copilot AI)
• Proficiency in SQL, including advanced query techniques
• Experience with version control systems (e.g., Git, Github, Jenkins)
• 6+ years of proficiency in Python and Jupyter notebooks. Experience with other languages such as R, and Scala is a plus but not necessary.
• Experience developing and assessing AI/ML models and ensembles
• Support the seamless integration of multi-media data processing into platform data pipelines
• Experienced in planning, setting-up, running and reporting on AI/ML experiments.
• Experience building feature repositories for AI-ML model training
• Project work in deep learning, transformers, computer vision, NLP, or chatbot development
• Experience in developing Generative AI applications especially using LLMs in domains such as NLP and image processing
• Knowledge of modern software design patterns (e.g., microservices, edge computing)
• Experience working with LLM frameworks and foundation models like LLaMa-3 and experience working with LLM model repositories like Huggingface
• Familiarity with MLOps practices and tools for model versioning and experiment tracking
• Experience identifying appropriate AI/ML models for a problem and using appropriate techniques to evaluate performance to choose the best model
• Experience with techniques for tuning model parameters to application data and conditions

Abilities

Desired Qualifications

• Having experience and a good understanding of Ux, Human-AI teaming, human factors in AI and software systems
• Published research papers or patents in the field of AI/ML
• Knowledge of Agentic AI Systems (e.g. AutoGen, LangGraph, LangChain, CrewAI etc.)
• Experience with Knowledge Graphs tools and techniques
• Experience with federated learning or privacy-preserving machine learning techniques
• Knowledge of data visualization techniques and tools
• GPU programming experience