Full stack Engineer
17 hours ago
As a Full Stack Engineer, you will work within the development team to build the annotation platform on both sides front-end and back-end. Collaborating with Product Managers, Architects and Software Engineers to research, design, implement and improve functionalities of the annotation platform as part of a Big Data analytic system.
Key responsibilities
- Design, develop, test, refactor and scale the next-gen data analytics platform, that provides data management, ETL pipelines, ML models integrations, rich visualizations, and information management around that.
- Be proactive in prototyping new ideas/components; Turn existing POC-level components into production-grade.
- Participate in code reviews and thoughtfully provide constructive feedback.
- Taking ownership of the whole vertical of certain functional area.
- Increase and maintain test coverage.
- Participate in overall architecture discussion meetings.
- Provide clean trail of activity – source control, issue tracking, documentation.
· Comply with QHSE (Quality Health Safety and Environment), Business Continuity, Information Security, Privacy, Risk, Compliance Management and Governance of Organizations policies, procedures, plans and related risk assessments.
RequirementsRequirements
- Computer science background, excellent knowledge of common data structures, and algorithms.
- 7+ years of experience building backend (java) and SPA web applications (react).
- Knowledge of web fundamentals: protocols, modern web standards.
- Pristine knowledge of modern React (composition patterns, hooks, data access), complex state management (Redux/Mobx).
- Experience wrapping existing JS libraries (SKDs) with framework abstractions.
- Solid web foundation knowledge (HTML, DOM CSS), experience with Tailwind is a plus
- Strong knowledge of Java platform (JSCP and/or Oracle certified professional Java SE11 will be a huge plus).
- Strong experience working with core Spring components (Security, Data/JPA, Web) and low level JDBC.
- Experience building durable long-running processing pipelines, task orchestration, scheduling, etc..
- Experience and passion in application profiling and low-level optimizations
- Fluent SQL is a must.
Ideally, it would be preferred if you also have
- Big data experience (Spark, Flink, Kafka, S3)
- Experience using, integrating etc… AI/ML models, knowledge of Python and common ML libs.
- Experience building durable processing pipelines with
- Experience working with column oriented OLAP engines (Clickhouse)
- Experience integrating ML models into the custom data pipelines.
- Experience using Docker/Kubernetes/MLO
Competitive Salary
Class A Medical Insurance
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