AI/ML Engineer for AI apps development

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.

A healthier future. That’s what drives us.  

We are looking for a highly skilled Artificial Intelligence (AI) / Machine Learning (ML) Engineer with expertise in building AI-powered applications. We will be building AI & GenAI solutions end-to-end: 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 end-user applications, focusing on user experience, and real-time performance

• Algorithm Development: Design, develop, customize, optimize, and fine-tune LLM-based and other AI-infused 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 Fine-Tuning and Customization: Fine-tune pre-trained LLMs to specific business needs, leveraging prompt engineering, transfer learning, and few-shot techniques to enhance model performance in real-world scenarios

• End-to-End Pipeline Development: Build and maintain production-ready end-to-end 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 cloud-based 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 fine-tuning 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 5-7 years of experience and hold B.Sc., B.Eng., M.Sc., M.Eng., Ph.D. or D.Eng. 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 model-based applications

• Technical Skills: Advanced proficiency in Python and experience with deep learning frameworks such as PyTorch or TensorFlow; expertise with Transformer architectures; hands-on experience with LangChain or similar LLM frameworks; experience with designing end-to-end RAG systems using state of the art orchestration frameworks (hands on experience with fine-tuning 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.
 

A healthier future drives us to innovate. Together, more than 100’000 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 life-changing healthcare solutions that make a global impact.

Let’s build a healthier future, together.