Job Description

San Francisco (*remote optional)

PLEASE - NO CONSULTANTS OR RECENT GRADS!

Our client has built an AI platform for business users, not just data scientists.

TECHNICAL SKILLS REQUIRED: C++ or Golang, Cloud (AWS or GCP), Machine Learning (ML) Infrastructure

This Artificial Intelligence platform manages unstructured data, such as documents, videos, images, audio, and webpages, and by understanding the context and attributes, bridges this information into a structured format.

REQUIRED SKILLS/EXPERIENCE:

• 4+ YEARS of industry experience in a systems infrastructure or software engineering role
• BACHELOR'S/MASTER'S/Graduate degree in Computer Science (or equivalent)
• Professional experience with distributed, compiler, database, operating, and/or cloud systems
• Professional experience with C++ OR GOLANG
• Interest in a wide variety of technical projects, ranging from developing ML INFRASTRUCTURE to scaling their analytics engine
• Experience shipping infrastructure software in a production environment
• Experience working with AWS OR GCP
• Attention to detail and care for writing high-quality, clean, and scalable code

THE OPPORTUNITY

This client is building an AI-POWERED DATA INTELLIGENCE PLATFORM that processes millions of images, videos, and documents along with their associated data records.

With a fast-growing customer base, they are hiring for a SOFTWARE ENGINEER, DATABASE ENGINE to help optimize their existing systems as well as oversee the design, architecture, and implementation of new systems that will improve how customer data is incrementally processed, updated, stored, and indexed for high-performance querying. Successful candidates will leverage their deep expertise in SYSTEMS DESIGN, STORAGE ENGINEERING, DATABASE INTERNALS, AND/OR LANGUAGE DESIGN FOR NEW CAPABILITIES AND FEATURES.

RESPONSIBILITIES:

• Upholding a high standard of code quality through code reviews and extensive testing
• Apply systems engineering fundamentals to optimize efficiency and increase processing throughput
• Scaling the engine to process petabyte streams of image and video data in real-time by utilizing lambda computing and compression techniques
• Increasing inference efficiency by identifying and addressing performance bottlenecks
• Design solutions to address hard storage, indexing, ingestion, and querying problems, unique to image and video data processing