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Software Engineer, Compute

Tecton

Saas

51-200

San Francisco, CA, USA

About the job

Overview:

At Tecton, we solve the complex data problem in production machine learning. Tecton’s feature platform makes it simple to activate data for smarter models and predictions. Tecton abstracts away the complex engineering to speed up innovation.
Tecton’s founders developed the first Feature Store when they created Uber’s Michelangelo ML platform, and we’re now bringing those same capabilities to every organization in the world.
Tecton is funded by Sequoia Capital, Andreessen Horowitz, and Kleiner Perkins, along with strategic investments from Snowflake and Databricks. We have a fast-growing team that’s distributed around the world, with offices in San Francisco and New York City. Our team has years of experience building and operating business-critical machine learning systems at leading tech companies like Uber, Google, Meta, Airbnb, Lyft, and Twitter.
We are building Rift - a new fully managed compute environment that allows data scientists to construct powerful batch and streaming feature pipelines in Python. This differs radically from technologies like Spark, which have a steep learning curve and significant overhead to manage, operate, and debug. Our new environment leverages popular open-source technologies such as Ray, Arrow, and DuckDB.
As a staff-level engineer building Tecton’s managed compute, you’ll play a critical role in architecting, designing, and scaling our first-ever managed compute platform that will serve as a compute engine used by every Tecton customer. As part of this team, you will be working in one or more of the following areas to build the next generation of Tecton infrastructure:

Distributed compute and resource management
Query optimization and distributed execution
Cross-platform integrations with state-of-the-art data platforms such as Snowflake and BigQuery
Fault-tolerant workloads on a lambda-based architecture
Data security

Responsibilities

Own and lead large technical domains starting from the problem definition and technical requirements along with implementation and maintenance
Lead multi-engineer projects of strategic importance to Tecton spanning cross-functional teams including design, product management, and other engineering teams
Drive efforts to improve engineering practices, tooling, and processes along with mentorship for senior engineers
Develop a deep understanding of the fundamental problems our customers face in building ML systems
Be a generalist as needed. We’re a small, but growing engineering team and each engineer needs to be versatile
Reinforce Tecton’s “Fast, but Focused” core value

Qualifications and Values

7+ years of experience in building product software systems
2+ years of technical leadership experience for a group of engineers
Experience working in large Python, Java, Kotlin, or Go codebases and running cloud-native production systems using Kubernetes, AWS, and Docker
Experience with distributed systems, SQL, and NoSQL databases
Bias to action and passion for delivering high-quality solutions
Strong communication and ability to write detailed technical specifications
Excitement about coaching and mentorship of junior engineers
BSc, MS or PhD in Computer Science or related fields