Job description

Hume AI is seeking a talented senior software engineer with strong experience in backend services and cloud infrastructure platforms who is interested in working with our team to build state-of-the-art audio models and evaluation tools. Join us in the heart of New York City and contribute to our endeavor to ensure that AI is guided by human values, the most pivotal challenge (and opportunity) of the 21st century. About Us Hume AI is a Series B startup dedicated to building artificial intelligence that is directly optimized for human well-being. As the first company to release speech language models, we’re focused on expanding our research to encompass audio understanding models and evaluation platforms for enterprises. Our goal is to enable a future in which technology draws on an understanding of human emotional expression to better serve human goals. As part of our mission, we also conduct groundbreaking scientific research, publish in leading scientific journals like Nature , and support a non-profit, The Hume Initiative, that has released the first concrete ethical guidelines for empathic AI ( www.thehumeinitiative.org ). You can learn more about us on our website ( hume.ai ) and read about us in WIRED , Forbes , and Venturebeat . About the Role As a Senior Platform Engineer, you will work directly with our team of research scientists, machine learning engineers, and designers to improve the services that allow us to deliver expression measurement, expression generation, and empathic foundation models in a number of groundbreaking applications. You will support cutting-edge research by contributing to the design, construction, and maintenance of a modern and efficient cloud AI infrastructure and the applications that run on it. You will be expected to operate with a high degree of autonomy, make sound architectural decisions, and take ownership of systems from design through production. Responsibilities Write clear and concise code to extend functionality on our platform and backend services. Architect and implement systems that enable new features and improvements of our API. Own the design and evolution of our cloud infrastructure, from deployment pipelines to production services. Communicate, collaborate, and grow alongside our engineering team. Champion well-tested, highly observable software with a focus on reliability and latency. Requirements 5+ years of experience in developing backend services. Expertise working with compute and storage on a cloud platform (e.g. GCP, AWS). Experience in Kotlin/Spring, Typescript/Express, Python/FastAPI, or Rust. Deep understanding of modern deployment strategies utilizing cloud technologies (e.g. blue/green, canary deployments, etc). Familiarity with service deployment tooling (especially Kubernetes, Terraform, Argo, Docker). History building and maintaining highly available SaaS products which ensure scalability, performance, and observability. Excellent communication and collaboration skills. Bonus Experience with machine learning concepts. Experience with relational databases (PostgreSQL, BigQuery, etc.). Application Note Please apply only to the position that best aligns with your qualifications. If you submit multiple applications or have applied within the past 6 months, only your initial submission will be considered. Annual Salary $180,000 — $230,000 USD

Requirements

Must-haves

Write clear and concise code to extend functionality on our platform and backend services.
Architect and implement systems that enable new features and improvements of our API.
Own the design and evolution of our cloud infrastructure, from deployment pipelines to production services.
Communicate, collaborate, and grow alongside our engineering team.
Champion well-tested, highly observable software with a focus on reliability and latency.
5+ years of experience in developing backend services.
Expertise working with compute and storage on a cloud platform (e.g. GCP, AWS).
Experience in Kotlin/Spring, Typescript/Express, Python/FastAPI, or Rust.
Deep understanding of modern deployment strategies utilizing cloud technologies (e.g. blue/green, canary deployments, etc).
Familiarity with service deployment tooling (especially Kubernetes, Terraform, Argo, Docker).
History building and maintaining highly available SaaS products which ensure scalability, performance, and observability.
Excellent communication and collaboration skills.

Nice-to-haves

Experience with machine learning concepts.
Experience with relational databases (PostgreSQL, BigQuery, etc.).
Application Note

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningapigcpawskotlintypescriptpythonrustkubernetesdocker

Platform: greenhouse
Effort: quick