About the role
Data and ML infrastructure: Design and implement scalable data and ML infrastructure using modern cloud and on-prem distributed technologies and frameworks. Data Pipeline Development: Design, develop and maintain scalable and efficient data pipelines to collect, process and store large volumes of data from various sources. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field
- Experience : 3+ years of experience in data & ML platform engineering or a similar role
- Proficiency in programming languages such as Python, Go, Java, or Rust
- Strong knowledge of containerization technologies (e.g. Docker) and orchestration systems (e.g. Kubernetes) in production environments
- Experience with SQL,database management systems (e.g., MySQL, PostgreSQL, SQL Server), data modeling and schema design
- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services, with a focus on Google Cloud. Google Cloud certification is preferred
More about this role
As a Data & ML Platform Engineer, you will play a critical role in designing, building and maintaining the infrastructure that powers our data processing pipelines and machine learning workflows that support our data-driven initiatives, as well as supporting the evolution of our Data & AI Platform. You will work at the intersection of data engineering, MLOps, and platform development and ensure that our data & AI infrastructure is robust, scalable and efficient. The ideal candidate will have a strong background in platform engineering, with experience in data science, machine learning and or data engineering.
Data and ML infrastructure: Design and implement scalable data and ML infrastructure using modern cloud and on-prem distributed technologies and frameworks.
Data Pipeline Development: Design, develop and maintain scalable and efficient data pipelines to collect, process and store large volumes of data from various sources.
Database Management : Manage and optimize databases and data warehouses to ensure data integrity, performance and availability.
Data Integration : Integrate data from multiple sources, including APIs, databases and external data providers, to create unified...
Browse similar: AI jobs · AI startup jobs · Startup jobs · Remote jobs