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Senior AI Engineer (ML & Data)

Pay
Pay not listed
Work setting
Not stated
Employment
Not stated

What you’ll work on

Full posting
  • Design, build and deploy AI agents end to end, from spec to production

  • Build agents and AI features on top of client data in Databricks

  • Own shipped agents: monitoring, evals, cost and failure handling

  • Ship early and iterate on feedback from real users

  • Turn loose problems from non-engineering stakeholders into clear requirements

From the employer’s posting
Design, build and deploy AI agents end to end, from first spec to production.
Build agents and AI features on top of the client’s data in Databricks.
Own what you ship once it’s live: monitoring, evals, cost and failure handling.
Ship early and iterate on feedback from real users.
Work with product, support and engineering stakeholders to turn loose problems into clear requirements.

What you’ll bring

All qualifications

Core experience

  • Machine learning or AI engineering background
  • Track record of shipping agents and AI features to production
  • Hands-on Databricks experience with batch and streaming pipelines
  • Strong Python with LLM APIs and MCP experience
  • Cloud experience in Azure or AWS
Qualification wording
Machine learning or AI engineering background.
A track record of shipping agents and AI features to production, with users who rely on them today.
Hands-on experience with Databricks, developing and managing batch and streaming pipelines.
Strong Python, with experience building with LLM APIs and MCP.
Cloud experience in Azure or AWS.

Benefits in the posting

Full benefits wording
  • About us In 2010, our founders dreamed up a company that could positively impact the world. Since then, we've been in permanent evolution: from business consulting to innovation and design, and now to building amazing digital products powered by AI. We scaled globally, launched AI Labs and Reshape Studios, and claimed our space as an AI consulting firm — helping organizations move from pilots to production through accountable AI. Today, we're expanding our impact across industries, driving real AI adoption through accountability, governance, and value at scale. Dreamers first, builders always.

From the employer’s posting.

Apply at Arionkoder

Posting record

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Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 2, 20261 day ago
Recorded sightings
3
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 1

Early. Similar jobs usually come down between day 6 and day 69.

From 4,284 similar postings that came down. Coming down is not always a hire.

Arionkoder is hiring

3 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • AWS
  • Azure
  • Databricks
  • MLflow
  • Terraform
Where the posting names them
- You use evals and data to decide when an agent is ready to ship and to measure whether it’s succeeding once live. - Strong Python, with experience building with LLM APIs and MCP. - Experience with agent frameworks or SDKs, and knowing when not to use one.
- Hands-on experience with Databricks, developing and managing batch and streaming pipelines. - Cloud experience in Azure or AWS. - You use evals and data to decide when an agent is ready to ship and to measure whether it’s succeeding once live.
- Work with product, support and engineering stakeholders to turn loose problems into clear requirements. - Build agents and AI features on top of the client’s data in Databricks. - Own what you ship once it’s live: monitoring, evals, cost and failure handling.
- A track record of shipping agents and AI features to production, with users who rely on them today. - Hands-on experience with Databricks, developing and managing batch and streaming pipelines. - Cloud experience in Azure or AWS.
- Processing complex documents with LLMs (OCR, extraction). - MLOps tools such as MLflow. - Background in logistics, transportation or compliance.
Nice to have: - Owning deployment of what you build: CI/CD, infrastructure as code (Terraform) and monitoring. - Processing complex documents with LLMs (OCR, extraction).

Your next step

Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

Arionkoder is an AI consulting firm helping companies build, embed, and own AI systems that drive real business outcomes. We combine Product Development, Artificial Intelligence, and Team Augmentation to craft digital products and solutions that create lasting impact — guided by a human-centric approach and a commitment to pushing the boundaries of what technology can do.

We’re hiring a contract AI engineer with a machine learning background who builds, deploys and operates AI agents in production on top of large datasets, using leading-edge agentic development practice to ship quickly. Our client builds AI agents and products for the trucking and fleet compliance space, used by both its customers and its internal teams. Agents work across tolling and millions of compliance documents, on top of more than 10 years of toll, inspection, safety and vehicle data. What you ship affects revenue, safety and compliance directly.

 

Responsibilities:

  • Design, build and deploy AI agents end to end, from first spec to production.
  • Ship early and iterate on feedback from real users.
  • Work with product, support and engineering stakeholders to turn loose problems into clear requirements.
  • Build agents and AI features on top of the client’s data in Databricks.
  • Own what you ship once it’s live: monitoring, evals, cost and failure handling.
  • Help the team move faster by bringing in and spreading best practices in agentic engineering.

How you’ll work:

  • Use coding agents as your main way of building software: define the work, check what agents produce and make the calls that matter.
  • Break work into pieces an agent can finish and you can verify, and run several agents in parallel.
  • Rely on tests, CI and agent review so speed doesn’t cost quality.
  • When something goes wrong, improve your setup so it doesn’t happen again, and package what works as reusable skills for the team.

Requirements:

  • Machine learning or AI engineering background.
  • A track record of shipping agents and AI features to production, with users who rely on them today.
  • Hands-on experience with Databricks, developing and managing batch and streaming pipelines.
  • Cloud experience in Azure or AWS.
  • You use evals and data to decide when an agent is ready to ship and to measure whether it’s succeeding once live.
  • Strong Python, with experience building with LLM APIs and MCP.
  • Experience with agent frameworks or SDKs, and knowing when not to use one.
  • You already use coding agents as your main way of building software.
  • You work independently, gather requirements from non-engineering stakeholders and give specific answers. When you don’t know something, you say so.
  • Advanced English, written and oral.

Nice to have:

  • Owning deployment of what you build: CI/CD, infrastructure as code (Terraform) and monitoring.
  • Processing complex documents with LLMs (OCR, extraction).
  • MLOps tools such as MLflow.
  • Background in logistics, transportation or compliance.

 

 

Important:  

Remote, LATAM · Overlap with 9am–5pm US Eastern

Interviews are hands-on: expect to walk through something you’ve built and shipped, in detail.

Perks

💵 Monthly USD Service Fee
🌴 20 business days of paid Agreed Time Off—Annual + 6 Local Holidays
🐣Caregiver Time Off
💻A dynamic remote work culture. You can work from anywhere!
🚀An entrepreneurial environment.

 

About us
In 2010, our founders dreamed up a company that could positively impact the world. Since then, we've been in permanent evolution: from business consulting to innovation and design, and now to building amazing digital products powered by AI. We scaled globally, launched AI Labs and Reshape Studios, and claimed our space as an AI consulting firm — helping organizations move from pilots to production through accountable AI. Today, we're expanding our impact across industries, driving real AI adoption through accountability, governance, and value at scale. Dreamers first, builders always.

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Location & working pattern

LATAM

Important: Remote, LATAM · Overlap with 9am–5pm US Eastern Interviews are hands-on: expect to walk through something you’ve built and shipped, in detail.
More source context
Perks 💵 Monthly USD Service Fee 🌴 20 business days of paid Agreed Time Off—Annual + 6 Local Holidays 🐣Caregiver Time Off 💻A dynamic remote work culture. You can work from anywhere! 🚀An entrepreneurial environment. About us In 2010, our founders dreamed up a company that could positively impact the world. Since then, we've been in permanent evolution: from business consulting to innovation and design, and now to building amazing digital products powered by AI. We scaled globally, launched AI Labs and Reshape Studios, and claimed our space as an AI consulting firm — helping organizations move from pilots to production through accountable AI. Today, we're expanding our impact across industries, driving real AI adoption through accountability, governance, and value at scale. Dreamers first, builders always.
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