Machine Learning Associate Advisor - HIH - Evernorth

Overview

Embed with business and product development teams to ship production generative and agentic AI systems on large language models, supporting healthcare applications at Evernorth.

What you'll do

• 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 and AI DLC construction, where AI proposes architecture, code, and tests and 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.

What you'll need

• 9+ years of total experience.
• 5+ years of experience in Fullstack development (Frontend, Backend Services, DB and Cloud).
• 5+ years of programming experience in Python, computer vision, self-supervised learning, transfer learning, and reinforcement learning.
• 2+ years in developing Agentic AI solutions and their 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.
• Degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Strong knowledge of data structures, algorithms, and software engineering principles.
• Strong knowledge of 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.
• Proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment.
• Front-end: proficiency in HTML/CSS/JavaScript and frameworks such as React, with basic understanding of UI/UX design principles.
• Back-end: proficiency in Python and experience building and consuming RESTful, Flask, FastAPI, and GraphQL APIs.
• Databases: knowledge of SQL and NoSQL databases, including MySQL, PostgreSQL, and MongoDB.
• DevOps and cloud: experience with Docker and Kubernetes/OpenShift, CI/CD pipelines using GitHub Actions, security best practices (IAM, encryption, network security), and hands-on AWS experience deploying applications and AI models.
• Machine learning and deep learning: understanding of algorithms, neural networks, supervised and unsupervised learning, and frameworks such as TensorFlow, PyTorch, and Keras.
• Generative models: knowledge of GANs, VAEs, and Transformers.
• NLP: knowledge of NLP techniques and libraries (e.g., spaCy, NLTK, Hugging Face Transformers) for text generation.
• Model deployment: experience with TensorFlow Serving, TorchServe, or cloud-based solutions such as AWS SageMaker or Google AI Platform.
• Hands-on knowledge of prompt engineering, finetuning, and RAG.
• Hands-on knowledge of building agents and agentic workflows.
• Proficiency with GitHub and version control workflows.
• Understanding of agile methodologies, testing, and code review practices.

Nice to have

• Experience working with recommendation engines, data pipelines, or distributed machine learning.
• 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.

Details

• Full-time position, working 45 hours per week.
• Expected overlap with US hours as appropriate.
• Primarily based in the Innovation Hub in Hyderabad, India, with flexibility to work remotely as required.