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Staff Software Engineer, Tecton Compute

TectonNy / Seattle, United States | Wa / Toronto / San Francisco, California, United StatesRemote, Onsite
This job is no longer open
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

$216,000 - $258,000 a yearThe estimated US base salary range for this position is $216,000 - $258,000 annually for employees based within California & New York. In addition to base salary, we offer competitive equity & comprehensive benefits such as medical, dental, vision, life, 401(K), flexible paid time off, 10 paid holidays each calendar year, sick time, leave of absence as per the FMLA and other relevant leave laws. Individual compensation packages are based on multiple factors such as location, level, role scope, and complexity, as well as additional job-related factors such as skills, experience, and expertise.Tecton values diversity and is an equal opportunity employer committed to creating an inclusive environment for all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other applicable legally protected characteristics.  If you would like to request any accommodations from the application through to the interview, please contact us at recruitingteam@tecton.ai.

This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. Apply for this job

This job is no longer open

Life at Tecton

Founded by the team that created the Uber Michelangelo platform, Tecton provides an enterprise-ready feature store to make world-class machine learning accessible to every company. Machine learning creates new opportunities to generate more value than ever before from data. Companies can now build ML-driven applications to automate decisions at machine speed, deliver magical customer experiences, and re-invent business processes. But ML models will only ever be as good as the data that is fed to them. Today, it's incredibly hard to build and manage ML data. Most companies don't have access to the advanced ML data infrastructure that is used by the internet giants. So ML teams spend the majority of their time building custom features and bespoke data pipelines, and most models never make it to production. We believe that companies need a new kind of data platform built for the unique requirements of ML. Our goal is to enable ML teams to build great features, serve them to production quickly and reliably, and do it at scale. By getting the data layer for ML right, companies can get better models to production faster to drive real business outcomes.
Thrive Here & What We Value1. Diversity and equal opportunity employment2. Comprehensive benefits package (medical, dental, vision, life insurance, 401(k), flexible paid time off, eight paid holidays annually, sick leave, FMLA-compliant leaves)3. Global team with offices in San Francisco and New York City4. Venture capital funding from Sequoia Capital, Andreessen Horowitz, Kleiner Perkins, Snowflake, Databricks5. Emphasis on innovation and technical expertise
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