At Roche you can show up as yourself embraced for the unique qualities you bring. Our culture encourages personal expression open dialogue and genuine connections where you are valued accepted and respected for who you are allowing you to thrive both personally and professionally. This is how we aim to prevent stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche where every voice matters.

The Position

A healthier future. Thats what drives us.

We are looking for a highly skilled Artificial Intelligence (AI) / Machine Learning (ML) Engineer with expertise in building AIpowered applications. We will be building AI & GenAI solutions endtoend: from concept through prototyping production to operations.

The Opportunity:

• Generative AI Application Development: Collaborate with developers and stakeholders in Agile teams to integrate LLMs and classical AI techniques into enduser applications focusing on user experience and realtime performance

• Algorithm Development: Design develop customize optimize and finetune LLMbased and other AIinfused algorithms tailored to specific use cases such as text generation summarization information extraction chatbots AI agents code generation document analysis sentiment analysis data analysis etc.

• LLM FineTuning and Customization: Finetune pretrained LLMs to specific business needs leveraging prompt engineering transfer learning and fewshot techniques to enhance model performance in realworld scenarios

• EndtoEnd Pipeline Development: Build and maintain productionready endtoend ML pipelines including data ingestion preprocessing training evaluation deployment and monitoring; automate workflows using MLOps best practices to ensure scalability and efficiency

• Performance Optimization: Optimize model inference speed reduce latency and manage resource usage across cloud services and GPU/TPU architectures

• Scalable Model Deployment: Collaborate with other developers to deploy models at scale using cloudbased infrastructure (AWS Azure) and ensuring high availability and fault tolerance

• Monitoring and Maintenance: Implement continuous monitoring and refining strategies for deployed models using feedback loops and e.g. incremental finetuning to ensure ongoing accuracy and reliability; address drifts and biases as they arise

• Software Development: Apply software development best practices including writing unit tests configuring CI/CD pipelines containerizing applications prompt engineering and setting up APIs; ensure robust logging experiment tracking and model monitoring

Who are:

• Minimum overall 57 years of experience and hold . . . . Ph.D. or . in Computer Science or equivalent degree.

• Experience: 3 years of experience in AI/ML engineering with exposure to both classical machine learning methods and language modelbased applications

• Technical Skills: Advanced proficiency in Python and experience with deep learning frameworks such as PyTorch or TensorFlow; expertise with Transformer architectures; handson experience with LangChain or similar LLM frameworks; experience with designing endtoend RAG systems using state of the art orchestration frameworks (hands on experience with finetuning LLMs for specific tasks and use cases considered as an additional advantage)

• MLOps Knowledge: Strong understanding of MLOps tools and practices including version control CI/CD pipelines containerization orchestration Infrastructure as Code automated deployment

• Deployment: Experience in deploying LLM and other AI models with cloud platforms (AWS Azure) and machine learning workbenches for robust and scalable productizations

• Practical overview and experience with AWS services to design cloud solutions familiarity with Azure is a plus; experience with working with GenAI specific services like Azure OpenAI Amazon Bedrock Amazon SageMaker JumpStart etc.

• Data Engineering: Expertise in working with structured and unstructured data including data cleaning feature engineering with data stores like vector relational NoSQL databases and data lakes through APIs

• Model Evaluation and Metrics: Proficiency in evaluating both classical ML models and LLMs using relevant metrics

Relocation benefits are not available for this posting.

Who we are

A healthier future drives us to innovate. Together more than 100000 employees across the globe are dedicated to advance science ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities foster creativity and keep our ambitions high so we can deliver lifechanging healthcare solutions that make a global impact.

Lets build a healthier future together.