Technical Account Manager

Posted 8 Days Ago
Be an Early Applicant
Hiring Remotely in US
Remote
150K-204K Annually
5-7 Years Experience
Machine Learning
The Role
As a Technical Account Manager at Tecton, you will be responsible for guiding enterprise customers to accelerate their adoption of the Tecton platform, ensuring they receive anticipated value. You will work with customer stakeholders, advocate on their behalf internally, and drive key initiatives for growth.
Summary Generated by Built In

At Tecton, we solve the complex data problems in production machine learning. Tecton’s feature platform makes it simple to activate data for smarter models and predictions, abstracting 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.


As a Technical Account Manager at Tecton, you will be responsible for guiding our largest enterprise customers to accelerate their adoption of the Tecton platform, ensuring customers receive the value they anticipated. Tecton’s Unified Feature Platform is being implemented and used by both large global enterprises and cutting-edge digital natives.

The Technical Account Manager proactively works with a broad set of customer stakeholders to illustrate the value delivered through Tecton’s software and services. The TAM also serves as the internal voice of the customer, advocating on their behalf when working with other Tecton teams and partners and driving alignment across Support, Engineering, Sales, Marketing, and Product. You will also work with the broader team to identify and drive key initiatives, processes, tools, and programs to scale for growth.

If you are experienced in ML, data engineering, or data science and passionate about the success of your customers, this is an excellent opportunity. This position reports directly to the Head of Technical Services.

Responsibilities

  • Actively serve global accounts including some of the world’s leading organizations in financial services, insurance, media, e-commerce, and technology.
  • Drive value for customers by helping them achieve their business and technical outcomes.
  • Gain an understanding of customer’s use cases and machine learning goals to ensure Tecton is strategically aligned to their desired business outcomes.
  • Serve as the voice of the customer within Tecton
  • Build strong relationships with customer stakeholders and become a trusted advisor within assigned accounts
  • Joint planning and prioritization with the customer of all ML-based business initiatives
  • Regular communication of account status and issues to Tecton leadership
  • Learn Tecton and provide a basic level of training and best practices
  • Assess additional customer education needs and coordinate delivery of enablement
  • Identify product blockers to expansion or product offerings that would unlock new use cases
  • Support customers with new product capability enablement
  • Understand and prioritize feature requests based on customer needs and facilitate design meetings with the customer and product team
  • Shadow initial implementation for strategic accounts to ensure a smooth transition with the Professional Services team

Qualifications

  • 5+ years of proven experience as a Technical Account Manager or similar customer facing role, preferred in the data and ML domain.
  • Strong track record of managing a portfolio of customers to drive product adoption.
  • The ideal candidate has technical acumen and hands-on knowledge of data engineering, Machine learning, and the major cloud platforms (AWS, GCP, Azure)
  • Understanding of the current ML landscape (applications, tools, new research)
  • General knowledge of Python, SQL, enterprise software, and cloud data architectures

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 [email protected].


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.

Top Skills

Ml
The Company
HQ: San Francisco, CA
88 Employees
Hybrid Workplace
Year Founded: 2019

What We Do

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.

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