LatitudeHiring

Senior Engineering Manager, Scalable Machine Learning

  • Remote, United States
  • Lead
  • 2 weeks ago
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In one line

Lead a team that builds the data and training infrastructure for machine learning models, working closely with several platform teams.

About the role

The role sits between ML, jobs, cloud and high performance computing groups, so much of the work is setting strategy and settling shared-infrastructure tradeoffs across teams that do not report to you.

At a glance

Pay
Not stated in the posting
Remote scope
Remote, United States
Seniority
Lead
Skills
Machine learning, MLOps, Distributed Training, GPU Scheduling, Computer Vision, Robotics
Posted
6 Oct 2026
Last checked
20 Oct 2026

What you will do

  • Manage and mentor software engineers on the scalable ML infrastructure team
  • Own the multi-quarter plan for data generation, orchestration and distributed training
  • Represent the team in org planning and architecture decisions on shared infrastructure
  • Set MLOps standards for model artifacts, experiment tracking and deployment testing
  • Build partnerships with peer managers and architects on adjacent platform teams
  • Hold systems to a high reliability bar, including cross-team incident follow-up

What they look for

  • Bachelor's degree plus 10 years of experience, or a Master's plus 8 years
  • Background in computer engineering, computer science, electrical engineering or robotics
  • Experience managing engineering teams and setting technical strategy
  • Ability to resolve cross-team tradeoffs on GPU scheduling, storage and compute cost

How Keywordise applies for you

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ClaudeConnectorChatGPTConnectorMuseby Meta

Claude

  1. In Claude, open Settings, then Connectors, and choose Add custom connector.
  2. Name it Keywordise and paste the connector URL.
  3. Click Connect, log in to Keywordise and approve. Then send the prompt in a new chat.
Connector URL
https://keywordise.com/mcp

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ChatGPT

  1. In ChatGPT, open Settings, then Connectors. On plans that need it, turn on developer mode first.
  2. Add a new connector with the connector URL and choose OAuth. Leave the client ID and secret empty.
  3. Log in to Keywordise and approve. Then send the prompt in a new chat.
Connector URL
https://keywordise.com/mcp

Disconnect any time in your Keywordise settings.

Muse

  1. Open Muse (muse.ai or the app) and send it the message below.
  2. If Muse asks how to sign in, answer OAuth. Open the sign-in link it sends, log in to Keywordise and approve.
  3. Send the prompt. Muse asks before it sends anything.
Message for Muse
Add a custom connector called Keywordise. It is a remote MCP server at https://keywordise.com/mcp and uses OAuth. Give me the sign-in link.

Muse is available in the US only for now.

Prompt
Apply to Keywordise job xrgyexmlo7
How to connect

Questions about this job

Is this a remote job, and where can I work from?

The posting lists it as remote for people in the United States.

What does this job pay?

No pay range is stated in the posting.

What experience is needed?

It is a lead role. The posting asks for: bachelor's degree plus 10 years of experience, or a Master's plus 8 years; background in computer engineering, computer science, electrical engineering or robotics; experience managing engineering teams and setting technical strategy. Skills it names include Machine learning, MLOps, Distributed Training, GPU Scheduling.

How do I apply with Keywordise AI?

Press the Apply with Keywordise AI button and add your CV. Keywordise tailors your CV and cover letter to this posting and sends the application for you, with a free 7-day trial and no card.

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