MLOps Engineer:
About Sanofi: We are an innovative global healthcare company, driven by one purpose: we chase the miracles of science to improve people's lives. Our team, across some 100 countries, is dedicated to transforming the practice of medicine by working to turn the impossible into the possible. We provide potentially life-changing treatment options and life-saving vaccine protection to millions of people globally, while putting sustainability and social responsibility at the center of our ambitions. Sanofi has recently embarked on a vast and ambitious digital transformation program. A cornerstone of this roadmap is the acceleration of its data transformation and the adoption of artificial intelligence (AI) and machine learning (ML) solutions, to accelerate R&D, manufacturing, and commercial performance and bring better drugs and vaccines to patients faster, to improve health and save lives.
Who You Are: You are a dynamic MLOps Engineer interested in challenging the status quo to ensure seamless MLOps that scale up Sanofi's AI solutions for the patients of tomorrow. You are an influencer and leader who has deployed AI/ML solutions with technically robust lifecycle management (e.g., new releases, change management, monitoring, and troubleshooting) and infrastructural support. You have a keen eye for improvement opportunities and a demonstrated ability to deliver using software engineering and MLOps skills while working across the full stack and moving fluidly between programming languages and technologies.
Our vision for digital, data analytics and AI: Join us on our journey in enabling Sanofi's Digital Transformation through becoming an AI-first organization. This means:
AI Factory - Versatile Teams Operating in Cross Functional Pods: Utilizing digital and data resources to develop AI products, bringing data management, AI, and product development skills to products, programs, and projects to create an agile, fulfilling, and meaningful work environment.Leading Edge Tech Stack: Experience building products that will be deployed globally on a leading edge tech stack.World Class Mentorship and Training: Working with renowned leaders and academics in machine learning to further develop your skillsets.Job Highlights:
Work in agile pods to design and build cloud-hosted ML products with automated pipelines that run, monitor, and retrain ML Models.Design AI/ML apps and implement automated model and pipeline adaptation and validation working closely with data scientists and data engineers.Support life cycle management of deployed ML apps (e.g., new releases, change management, monitoring, and troubleshooting).Build processes supporting seamless MLOps (e.g., app monitoring, troubleshooting, life cycle management, and customer support).Walk stakeholders and solution partners through solutions and review product change and development needs.Maintain effective relationships with app user base to develop education and communication content as per life cycle events.Research and gain expertise on emerging tools and technologies. An enthusiasm to ask questions and try and learn new things is essential.Key Functional Requirements & Qualifications:
Experience in data science, statistics, software engineering, modular design, and design thinking.Experience developing CI/CD pipelines for AI/ML development, deploying models to production, and managing the lifecycle in a regulated environment.Experience building and deploying data science apps with large scale data and ML pipelines and architectures.Experience working in an agile pod supporting and working with cross-functional teams.Good understanding of ML and AI concepts and hands-on experience in development, deployment, and agile life cycle management of data science apps (MLOps).Ability to assess new technologies and compile architecture decision records (ADRs).Excellent communication skills in English, both verbal and in writing.Key Technical Requirements & Qualifications:
Bachelor's degree in Computer Science, Information Systems, Software Engineering, or another quantitative field and 3 years of relevant industry or academic experience.Ability to work across the full stack and move fluidly between programming languages and MLOps technologies (e.g., Python, Spark, R, DataBricks, Github, MLFlow, Airflow).Experience in cloud and high-performance computing environments (AWS preferred).Experience in AWS (e.g., S3, Lambda, EC2, CloudWatch) and other similar technologies (e.g., ELK stack, Snowflake, Informatica).Knowledge of SQL and relational databases, query authoring (SQL), and designing a variety of databases (e.g., Postgres SQL).Experience with visualization technologies (e.g., RShiny, Python DASH, Tableau, PowerBI).Experience in development, deployment, and operations of AI/ML modeling of complex datasets.Experience in developing and maintaining APIs (e.g., REST).El anuncio original lo puedes encontrar en Kit Empleo: https://www.kitempleo.es/empleo/129964905/rkt-295-mlops-engineer-barcelona/?utm_source=html
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