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Software Engineer, Collaboration

TectonCa / New York, United States | Ny / Buenos Aires / Bogota / Montevideo / Sao PauloRemote, 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.The Collaboration team is about focusing on the needs of larger enterprise customers and enabling them to leverage the full potential of a Feature Platform.

We make it easy for enterprise customers to manage, administer, and collaborate in the Tecton environment while meeting their security, compliance, and budgetary needs.

Responsibilities


  • Primary ownership of building Tecton’s identity management, access control, and data governance that protect the most sensitive data of our customers
  • Building out new capabilities for organizing, governing, and sharing features,  audit logging, consumption measurement, and usage analytics
  • Partnering with other teams to integrate the above with other Tecton capabilities

Qualifications


  • An engineer with 5+ years of backend experience (ex., Kotlin, Java, Python, Go, etc.) in Software Engineering
  • Passion for building delightful products and end-user UX
  • Excellent communication skills
  • Preferred: Data infrastructure (Kubernetes, Terraform, etc.) and cloud (AWS, GCP, Azure) experience
  • Preferred: Internal analytics experience
  • Preferred: Auth and Access control systems experience
  • Preferred: B2B SaaS and enterprise features experience
  • Preferred: Full stack experience

$189,000 - $258,000 a yearThe estimated US base salary range for this position is $189,000 - $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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