WoolpertHiring

AI/ML Engineer

  • Remote, United States
  • Senior
  • Posted 4 weeks ago
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In one line

Client-facing AI/ML engineer on a cloud solutions team, building Google Cloud AI systems for customers; hybrid, with some days in a US office.

About the role

Teams here tackle hard problems for clients in infrastructure, communities and technology. The job is hands-on delivery: research new Google AI tools, then turn them into working systems and trained users.

At a glance

Pay
Not stated in the posting
Remote scope
Remote, United States
Seniority
Senior
Skills
Gemini, Vertex AI, TensorFlow, BigQuery, Cloud Storage, Dataflow, Python
Visa
No sponsorship
Posted
6 Oct 2026
Last checked
2 Nov 2026

What you will do

  • Join client engineering teams, product owners and developers to keep projects on track
  • Run discovery sessions to pin down business needs, success measures and the solution shape
  • Design and build AI/ML pipelines on Google Cloud, from data intake to model monitoring

What they look for

  • Eight or more years in a customer-facing consulting role
  • Hands-on work with Gemini models, including integration, tuning and custom builds
  • Experience with Vertex AI, TensorFlow, BigQuery, Cloud Storage and Dataflow
  • Fluency in Python or NodeJS/ES6 plus AI/ML libraries
  • Knowledge of SDLC and Agile methods, with tools like Git and Jira

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
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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 senior role. The posting asks for: eight or more years in a customer-facing consulting role; hands-on work with Gemini models, including integration, tuning and custom builds; experience with Vertex AI, TensorFlow, BigQuery, Cloud Storage and Dataflow. Skills it names include Gemini, Vertex AI, TensorFlow, BigQuery.

How do I apply with Keywordise AI?

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WoolpertRemote, United States
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