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Machine Learning Senior Analyst

3 months ago

Hyderabad, India Evernorth Full time

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.

Role Title: Machine Learning Senior Analyst
Position Summary:

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. We are looking for Sr AI Engineers with strong engineering, full stack expertise to build the best fit solutions leveraging Large Language Models (LLMs) and Generative AI solutions. 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

Job Description & Responsibilities:

  • Build scalable software solutions using LLMs and other ML models to solve challenges in healthcare
  • Build enterprise grade AI solutions with focus on privacy, security, fairness.
  • Work with Product Development as a Generative Artificial Intelligence (AI) subject matter expert and architect and develop scalable, resilient, ethical AI solutions
  • Strong engineering skills to design the output from the AI with nodes and nested nodes in JSON or array, HTML formats as required This is critical so that the AI output can be consumed as is and displayed on the dashboard for accelerated development cycles.
  • Build extensible API Integrations, low code UI/UX solutions, with extremely short cycle times, to extract information from sources, integrate with GPT4, receive insights and make them available in intuitive, high performing dashboards
  • Build solutions that align with responsible AI practices.
  • Envision the solution outcomes to solve for the business problem with actionable insights and design viable solutions to meet the outcomes.
  • Understand how AI is interpreting the data set and use that understanding to build prompts that lead to expected outcomes
  • Architect and develop software or infrastructure for scalable, distributed systems and with machine learning technologies.
  • Work with frameworks(Tensorflow, PyTorch) and open source platforms like Hugging Face 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.
  • Understanding of various applications of generative AI like summarization, translation, conversational systems, retrieval augmented generation
  • 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.
  • Strong technical skills in machine learning and AI, especially natural language processing, generative models like GPT-3, DALL-E, etc. Understanding how these models work is crucial.
  • Solid delivery experience of at least one large scale solution leveraging Gen AI.
  • Experience with large-scale cloud infrastructure and services like AWS, GCP, Azure. Knowing how to build and deploy AI solutions leveraging cloud services.
  • Software engineering skills - Ability to build systems and infrastructure to deploy AI models into production applications and ensure effective integration.
  • Knowledge of AI Responsibility principles like safety, transparency, fairness and accountability. Assessing and mitigating risks from generative AI.
  • Architectural design ability - Design effective pipelines, processes, validation mechanisms for building enterprise-grade generative AI solutions.

Experience Required:

  • 3 years of Full stack engineering expertise with languages like C#, Python and Proficiency in designing architecture, building API Integrations, configuring and deploying cloud services, setting up authentication, monitoring and logging
  • 1 years of experience in a technical leadership role leading project teams and setting technical direction.
  • 1 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects

Experience Desired:

  • Experience in implementing enterprise systems in production setting for AI, computer vision, natural language processing. Exposure to self-supervised learning, transfer learning, and reinforcement learning is a plus.
  • Experience with information storage/retrieval using vector databases like pinecone.
  • Experience with designing scalable software systems for classification, text extraction/summary, data connectors for different formats(pdf, csv, doc, etc)
  • Experience with machine learning libraries and frameworks such as PyTorch or TensorFlow, Hugging Face, Lang chain, Llama Index.

Education and Training Required:

  • Degree in Computer Science, Artificial Intelligence, or a related field

Primary Skills:

  • Strong understanding and exposure in natural language generation or Gen AI like transformers, LLMs, text embeddings
  • Strong knowledge of data structures, algorithms, and software engineering principles.
  • Familiarity with cloud-based platforms and services, such as AWS, GCP, or Azure.

Additional Skills:

  • 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