Mlops Engineer - Q-881
Responder al anuncioMLOps EngineerAbout SanofiWe 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 into a vast and ambitious digital transformation program. A cornerstone of this roadmap is the acceleration of its data transformation and of 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 AreYou 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. Job HighlightsWork in agile pods to design and build cloud hosted, ML products with automated pipelines that run, monitor, and retrain ML ModelsDesign AI/ML apps and implement automated model and pipeline adaption and validation working closely with data scientists and data engineersSupport 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 reviewing product change and development needsMaintain effective relationships with app userbase to develop education and communication content as per life cycle eventsResearch and gain expertise on emerging tools and technologies. An enthusiasm to ask questions and try and learn new things is essentialKey Functional Requirements & QualificationsExperience in data science, statistics, software engineering, modular design and design thinkingExperience developing CI/CD pipelines for AI/ML development, deploying models to production, and managing the lifecycle in a regulated environmentExperience building and deploying data science apps with large scale data and ML pipelines and architecturesExperience working in an agile pod supporting and working with cross-functional teamsGood 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 writingKey Technical Requirements & QualificationsBachelor degree in Computer Science, Information Systems, Software Engineering or another quantitative field and 3 years of experience of relevant industry or academic experienceAbility 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, cloud watch) and other similar technologies (e. G. : ELK stack, Snowflake, Informatica)Knowledge of SQL and relational databases, query authoring (SQL) and designing 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 modelling of complex datasetsExperience in developing and maintaining APIs (e. G. : REST)#J-18808-Ljbffr
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