Full stack Engineer

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.

Requirements

Requirements

• 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 Temporal.io
• Experience working with column oriented OLAP engines (Clickhouse)
• Experience integrating ML models into the custom data pipelines.
• Experience using Docker/Kubernetes/MLO

Benefits

Competitive Salary

Class A Medical Insurance