Dedicated MLOps engineers for your offshore team.
Offshore MLOps engineers in Chiang Mai and Bangkok, working full time on your roadmap and managed by us. An MLOps engineer gets models out of notebooks and into production, and keeps them accurate as the data underneath them changes.
One agreement and one fixed monthly fee, with a service delivery manager in Thailand who runs your team day to day.
This role is part of a dedicated MLOps engineering team. It's staff augmentation, fully managed: take one role on its own, or the whole discipline as one delivery team.
One MLOps Engineer, assigned to your product and fully managed.
We assign an MLOps Engineer to your team full time and run everything around them: a service delivery manager who answers for the work, training and coaching, the office and equipment, and HR and payroll. The price below is for a mid-level MLOps Engineer; junior and senior levels are priced in your proposal, and how the monthly fee is built explains the arithmetic.
From price
One mid-level MLOps Engineer, full time, everything below included. All 27 things included ››
- MLOps engineer From USD 4,200 per month
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Service
We manage and develop the team
- A service delivery manager who runs the team and answers for delivery
- A 1:1 with our Head of Delivery every two weeks
- Weekly delivery scoring and monthly capacity reports
- A Talent Success Manager for every specialist
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HR
We are the employer
- Recruitment and technical assessment
- Employment contracts
- Salary and payroll
- Tax and social security
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Facilitation
We provide the workplace
- A desk in our own office in Chiang Mai or Bangkok
- A Workplace Experience Manager on site
- Team events through the year
- IT support
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Equipment
We supply the tools
- Laptop and hardware
- Software licences
- LinkedIn Learning access
- Device security and management
What an MLOps Engineer does on an MLOps team.
They work between your data scientists and your infrastructure team, in your cloud account, and own the path from trained model to production.
MLOps Engineer skills and technologies
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Building deployment pipelines for models, with versioning and rollback.
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Monitoring for drift and performance decay, which is the failure mode unique to machine learning.
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Automating retraining so model quality does not depend on someone remembering.
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Building reproducible training pipelines so a model can be rebuilt from scratch when needed.
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Managing the model registry so it is always clear which version is serving production traffic.
MLOps Engineer seniority levels.
Mid-level to senior. The role spans data science and infrastructure and needs credibility in both. Seniority is one of the inputs into how the monthly fee is built.
When your team needs an MLOps Engineer.
The right addition when models exist and no one owns them after deployment. Often paired with a machine learning or ML platform engineer. MLOps engineers join as part of MLOps engineering at Azendo.
What we look for in a dedicated MLOps Engineer.
We look for MLOps engineers who are credible with data scientists and infrastructure teams alike. They should build reproducible pipelines, watch for drift, and automate retraining so it runs on schedule.
Your remote MLOps Engineer's first three months.
- Weeks 1 to 2Reviewing your models, training code and deployment path.
- Weeks 3 to 6Building a deployment pipeline with versioning, rollback and a model registry.
- Months 2 to 3Adding drift monitoring and automated retraining for models in production.
Questions about adding an MLOps Engineer to your team.
Our models are in notebooks. Where do we start?
With one model and one deployment path, then build out from there.
How do you detect model drift?
By monitoring input distributions and output quality against a baseline, with alert thresholds agreed with your team.
Add remote MLOps engineers to your team.
Tell us your roadmap and your stack, and we'll come back with the right profile, the capacity and a start date. You can also talk to a service delivery manager first.
Add MLOps engineers to your remote team.
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