Mlops Data Engineer
Il y a 5 mois
We are partnering with an innovative global healthcare company, recently embarking on 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 Are**
You are a dynamic MLOps Engineer interested in challenging the status quo to ensure seamless MLOps that scale up 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 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 adaption 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 reviewing product change and development needs
- Maintain effective relationships with app user-base to develop education and communication content as per life cycle events
- Researching and gain expertise on emerging tools and technologies
- An enthusiasm to ask questions and try and learn new things is essential
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 Graduate degree in Computer Science, Information Systems, Software Engineering or another quantitative field Ability to work across the full stack and move fluidly between programming languages and MLOps technologies (e.g., Python, Spark, R, Metaflow, Github, MLFlow, Argo) Experience in cloud and high-performance computing environments Experience in AWS (e.g., S3, Lambda, EC2, cloud watch) and other similar technologies (e.g., ELK stack, Snowflake, Informatica) Knowledge of relational databases, query authoring (SQL) and designing variety of databases (e.g., Postgres SQL, Document store) Nice to have knowledge of visualization technologies (e.g., RShiny, Python DASH, Tableau, PowerBI, web framework) Experience in development, deployment and operations of AI/ML modelling of complex datasets Experience in developing and maintaining APIs (e.g., REST) Experience specifying infrastructure and Infrastructure as a code (e.g., docker, Kubernetes, EKS, Terraform) Experience in cloud-based ML engineering in an industrial setting within a global organization (technology company preferred) Experience on working within compliance (e.g., quality, regulatory - data privacy, GxP, SOX) and cybersecurity requirements is a plus For more senior roles, mentoring and/or technology evangelism/advocacy experience
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