About Evernorth: Evernorth Health Services, a division of The Cigna Group (NYSE: CI), creates pharmacy, care, and benefits solutions to improve health and increase vitality.

We relentlessly innovate to make the prediction, prevention, and treatment of illness and disease more accessible to millions of people.

Position Overview: We are looking for Machine Learning Engineer with strong experience on LLMs and frameworks to develop Gen AI solutions.

Good understanding on Deep learning and strong programming skills are required as part of this role.

Good to have full stack development expertise to evaluate new Large Language Models (LLMs) and make them available for the enterprise in a compliant and secure manner.

The work you do will impact millions of customers, members, and employers that rely on Cigna every day.

Extreme focus on speed to market and getting Products and Services in the hands of customer and passion to transform healthcare is key to the success of this role.

Responsibilities: Utilize Large Language Models (LLMs), Open Source, Machine Learning, and numerical programming frameworks, to build transformative solutions.

Understanding of AI Models, Large Language Models, and AI specialized infrastructure especially as it relates to AI trends and issues within businesses.

Work with Product Development as a Generative Artificial Intelligence (AI) subject matter expert and architect and develop scalable, resilient, ethical AI solutions.

Build solutions that align with responsible AI practices.

Work with both open-source models (Tensorflow, Py Torch, Hugging Face Transformers) cloud solutions, internal solutions and external partners to deliver the best solutions Optimize existing generative AI models for improved performance, scalability, and efficiency.

Develop and maintain AI pipelines, including data preprocessing, feature extraction, model training, and evaluation.

Qualifications Required Skills: Experience working with recommendation engines, data pipelines, or distributed machine learning.

Degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

Extensive experience in research with sequential modelling or generative AI, deep learning architectures, and Transformers, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.

Programming experience in C/C++, Java, Python, computer vision, self-supervised learning, transfer learning, and reinforcement learning.

Experience with machine learning libraries and frameworks such as Tensor Flow, Py Torch, or Keras.

Experience with natural language processing (NLP) techniques and tools, such as Spa Cy, NLTK, or Hugging Face.

Strong knowledge of data structures, algorithms, and software engineering principles.

Familiarity with cloud-based platforms and services, such as AWS, GCP, or Azure.

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.

Required Experience & Education: 8-11 Years of Experience Previous experience as Machine Learning Engineer / Prompt Engineer and strong programming skills.

Experience working within the healthcare industry is desirable.

Familiarity with healthcare-specific IT systems and industry regulations, such as Electronic Health Record systems and HIPAA, is an added advantage.

Desired Experience: Exposure to Gen AI and Cloud systems like AWS.

Location & Hours of Work: Full-time position, working 40 hours per week.

Expected overlap with US hours as appropriate Primarily based in the Innovation Hub in Hyderabad, India in a hybrid working model (3 days WFO and 2 days WAH) Equal Opportunity Statement: Evernorth is an Equal Opportunity Employer actively encouraging and supporting organization-wide involvement of staff in diversity, equity, and inclusion efforts to educate, inform and advance both internal practices and external work with diverse client populations.