Job
Description
Specialist IS Engineer for GEN AI solutions across various Process Development functions(Drug Substance, Drug Product, Attribute Sciences & Combination Products) in Operations functions is responsible for building cutting edge GEN AI solutions. The role involves working closely with Data Scientists developing, implementing and sustaining GEN AI solutions to help find relevant, actionable information quickly and accurately. Roles & Responsibilities: Possesses strong rapid prototyping skills and can quickly translate concepts into working code Conduct code reviews to ensure code quality and adherence to best practices. Create and maintain documentation on software architecture, design, deployment, disaster recovery, and operations. Identify and resolve technical challenges effectively. Stay updated with the latest trends and advancements Work closely with product teams, business team, and other key partners. Design, develop, and deploy applications that use LLMs like OpenAI GPT Build and maintain MLOps pipelines, including data ingestion, chunking, vectorization, feature engineering, model training, deployment, and monitoring Design, fine-tuning, and optimization of state-of-the-art LLMs for various applications, focusing on both performance and accuracy Implement DevOps/MLOps/LLMOps standard methodologies to automate ML workflows and improve efficiency. Develop and implement monitoring systems to track model performance and identify issues. Conduct testing and experimentation to optimize model performance. Review code and maintain strong standards and practices on the team Work closely with data scientists, engineers, and product teams to deliver ML solutions. Stay updated with the latest trends and advancements What we expect of you We are all different, yet we all use our unique contributions to serve patients. Basic Qualifications: Doctorate Degree OR Masters degree with 4 - 6 years of experience in Software Engineering, Data Science or Machine Learning Engineering OR Bachelors degree with 6 - 8 years of experience in I Software Engineering, Data Science or Machine Learning Engineering OR Diploma with 10 - 12 years of experience in Software Engineering, Data Science or Machine Learning Engineering Great foundation in machine learning algorithms and techniques Must-Have Skills: Expertise in Python and relevant ML libraries (e.g., Langchain, TensorFlow, PyTorch) Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops Excellent problem-solving skills and the ability to work with large, complex datasets. Experience in implementing Retrieval-Augmented Generation (RAG) pipelines, integrating retrieval mechanisms with language models. Experience in processing and leveraging unstructured data for GenAI applications Proven experience working with large language models (e.g., OPEN AI, LLAMA.). Experience in building, testing, and deploying machine learning models, particularly large language models, troubleshoot and optimize models. Experience in using cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment Preferred Qualifications: Solid understanding of Machine Learning (ML) workflows including ingesting, analyzing, transforming data and evaluating results to make meaningful predictions. Design, test, and deploy machine learning models, including LLMs, and develop scalable pipelines for both batch and real-time use cases. Professional Certifications: Machine Learning Certification (preferred on Databricks or Cloud environments). SAFe for Teams certification (preferred). Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals
