Machine Learning Associate Advisor

We are seeking a Machine Learning Associate Advisor to join our team transforming healthcare and improving the lives and vitality of millions of members we serve. You will leverage cutting-edge Artificial Intelligence (AI) and Machine Learning (ML) algorithms to develop AI-powered solutions for healthcare applications.

Responsibilities:

• Embed with Business and Product Development to ship production AI systems.
• Architect scalable, resilient generative and agentic AI solutions for the business.
• Build with large language models, open-source models, machine learning, and numerical frameworks.
• Maintain pipelines for preprocessing, feature extraction, model training, and evaluation.
• Build agentic workflows with tool limits, human oversight, and safe fallbacks.
• Optimize generative models for quality, scalability, latency, and efficiency.
• Apply responsible AI through use limits, evaluation, traceability, and human approval.
• Translate model, infrastructure, and business AI trends into architecture decisions.
• Practice AI-driven development: agents plan and build; humans approve critical decisions.
• Run AI DLC inception, Run AI DLC construction, AI proposes architecture, code, and tests; humans approve.
• Keep one traceable context from business intent through code, tests, and operations.
• Lead real-time team review of AI plans, designs, and generated code.
• Measure field outcomes and return supportable systems to Product Development.

Requirements:

• 9+ years of total experience.
• 5+ years of experience in Fullstack development (Frontend, Backend Services, DB and Cloud).
• 5+ Programming experience in Python, computer vision, self-supervised learning, transfer learning, and reinforcement learning.
• 2+ year in developing Agentic AI solutions and its integration with other systems.
• 2+ years of experience in deep learning architectures, and Transformers, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.

Qualifications:

• Experience working with recommendation engines, data pipelines, or distributed machine learning.
• Degree in Computer Science, Artificial Intelligence, Machine Learning, and related field.
• Experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.
• Experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.
• Strong knowledge of data structures, algorithms, and software engineering principles.
• Strong knowledge with AWS cloud-based platforms and services.
• Excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions.
• Strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.
• Possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment.