Position Overview You will be joining a team transforming healthcare and improving the lives and vitality of the millions of members we serve We leverage cutting edge Artificial Intelligence AI and Machine Learning ML algorithms to develop solutions for automated document processing and customer service chat bots Your focus will be developing the best fit solutions leveraging Large Language Models LLMs and Generative AI solutions including but not limited to BERT RoBERTA and GPT for a number of Natural Language Processing NLP tasks You will be working closely with business stakeholders Machine Learning Engineers to help us to transform the end to end value chain across various are The work you do will impact millions of customers members and employers that rely on Cigna every day Qualifications 5 - 8 years of experience in technology Experience working with recommendation engines data pipelines or distributed machine learning Degree in Computer Science Artificial Intelligence Machine Learning or a related field A Ph D is highly desirable 5 years of experience in research with sequential modeling or generative AI deep learning architectures and Transformers with a strong understanding of deep learning techniques such as GPT VAE and GANs 3 years of experience in a technical leadership role leading project teams and setting technical direction 5 years of experience working in a complex matrixed organization involving cross-functional or cross-business projects 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 TensorFlow PyTorch or Keras Experience with natural language processing NLP techniques and tools such as SpaCy NLTK or Hugging Face Robust 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 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 Architect and develop software or infrastructure for scalable distributed systems and with machine learning technologies Work with both open source models Tensorflow PyTorch 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 Develop clear and concise documentation including technical specifications user guides and presentations to communicate complex AI concepts to both technical and non-technical stakeholders Contribute to the establishment of best practices and standards for generative AI development within the organization About Evernorth Health Services Evernorth Health Services a division of The Cigna Group creates pharmacy care and benefit 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 Join us in driving growth and improving lives
📌 Machine Learning Lead Analyst - Hih - Evernorth (Andhra Pradesh)
🏢 The Cigna Group
📍 Andhra Pradesh
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