Engineering Manager, Active Learning

Deepgram

$130K — $180K *
US-AnywhereRemote in United States
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Proven experience managing and growing engineering teams.
  • Strong technical background in building solutions.
  • Ability to make scalable and thoughtful technical decisions.
  • Passion for good engineering practices and emerging technologies.
  • Experience navigating the challenges of a startup environment.
  • Strong practical experience with software architecture and implementation.

Responsibilities

  • Recruit, hire, and train top engineering talent.
  • Transform visions into detailed project plans with clear commitments and timelines.
  • Define and own the technical strategy for ML training pipelines.
  • Promote a robust engineering culture with a focus on standards and continuous improvement.
  • Collaborate with DataOps and Research to design and implement new services and products.
  • Coach and mentor engineers to achieve personal growth and team goals.

Benefits

  • Opportunity to work with cutting-edge technologies in machine learning.
  • Supportive company culture emphasizing personal and professional growth.
  • Collaboration with cross-functional teams to drive impactful projects.
  • Fast-paced, learning-oriented work environment.
  • Empowerment to make significant technical decisions within a growing startup.
Full Job Description
Opportunity

Deepgram is looking for an Engineering Manager to lead the design and implementation of Deepgram's internal data and ML training systems. You will lead a team of engineers in building crucial components for driving a data flywheel that powers fundamental product quality as well as a system for large-scale, distributed ML training on a HPC cluster. Your ability to partner effectively with leaders and ICs in Research and DataOps while leading talented engineers to build, maintain, and extend mission-critical systems will contribute significantly to Deepgram's competitive advantage. You will be a critical voice in Deepgram's DataOps, Research, and Engineering teams, driving high impact products from start to finish.

What You'll Do
  • Recruit, hire, train, and support top engineering talent to build a world-class team
  • Transform cross-functional visions into detailed project plans, ensuring clarity across teams on commitments, risks, and timelines
  • Define and own the technical strategy enabling acceleration of Deepgram's ML training pipelines
  • Promote a robust team engineering culture, including a focus on rigorous engineering standards as well as continuous improvement on team practices and processes
  • Partner with DataOps and Research to design and implement new services, features, and/or products end to end
  • Coach and mentor engineers to achieve high personal growth while delivering on ambitious team goals


You'll Love This Role If You
  • Thrive in a fast-paced, impact-driven environment where learning new skills on-the-fly is not only encouraged but a regular necessity
  • Enjoy balancing decisions about product and feature maturity to decide when to make minimally invasive changes versus when to incorporate detailed design work
  • See management as an opportunity to empower a team to solve big problems through your own grit, learning, and empathy


It's Important To Us That You Have
  • Proven experience managing and leading and growing a team with a consistent record of mentoring and coaching team members
  • A strong technical background building world class solutions
  • The ability to drive technical decisions in a scalable and thoughtful manner
  • Passion about good engineering practices, emerging technologies, and improving processes
  • A passion for navigating the team through the real-world constraints of a startup: how to build quickly, iterate frequently, and run experiments
  • Strong practical experience with software architecture and implementation, plus the ability to engage with an Engineering team to help build and scale the existing infrastructure


It Would Be Great if You Had
  • Experience working in high-growth startups
  • Familiarity with hybrid cloud models (bare-metal datacenters and cloud service providers) and scaled databases
  • Deep experience with machine learning training, inference, or both

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