Senior AI/ML Engineer

Software engineering is the application of engineering to the design, development, implementation, testing and maintenance of software in a systematic method. The roles in this function will cover all primary development activity across all technology functions that ensure we deliver code with high quality for our applications, products and services and to understand customer needs and to develop product roadmaps.

These roles include, but are not limited to analysis, design, coding, engineering, testing, debugging, standards, methods, tools analysis, documentation, research and development, maintenance, new development, operations and delivery. With every role in the company, each position has a requirement for building quality into every output. This also includes evaluating new tools, new techniques, strategies; Automation of common tasks; build of common utilities to drive organizational efficiency with a passion around technology and solutions and influence of thought and leadership on future capabilities and opportunities to apply technology in new and innovative ways. Generally work is self-directed and not prescribed.

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
• Works with less structured, more complex issues
• Serves as a resource to others
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

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