Backend Engineer- Inference Services

Company Operating Rhythm

Opportunity

Deepgram is looking for a Backend Software Engineer to join the Engine team to lead the design and implementation of Deepgram’s products. You will design and implement secure, robust, and scalable services for speech processing; efficient, distributed compute orchestration; optimized scheduling, and more. Your skill at building highly reusable code that overcomes technical challenges is paired with an intuition for delightful user experiences. You will be a critical voice in Deepgram’s Product and Engineering teams, driving high impact products from start to finish.

What You’ll Do

• Improve Deepgram’s core inference services including areas in networking, speech processing, audio transcoding, and latency and memory optimization
• Develop processes for measuring, building, and optimizing services to maximize system performance
• Debug complex system issues that include networking, scheduling, and high performance computing interactions
• Rapidly customize backend services to support our customer needs
• Partner with Product to design and implement new services, features, and/or products end to end

You’ll Love This Role If You

• Thrive in a fast-paced, impact-driven environment where learning new skills on-the-fly is not only encouraged but a regular necessity
• Enjoy balancing decisions about product and feature maturity to decide when to make minimally invasive changes versus when to incorporate detailed design work

It’s Important To Us That You Have

• 3+ years of experience in an industry role
• Programming experience in Rust (or C, C++), with competence in Python
• Excellent communication and organizational skills, both written and verbal.
• A high level of experience and understanding of version control; preferably git.
• Comprehensive experience with UNIX-style systems.

It Would Be Great if You Had

• Experience with modern machine learning, such as experience with a framework like Torch or implementation knowledge of architectures like CNNs, RNNS, and transformers
• Experience with audio processing