---
title: "Outsource TensorFlow Specialists for Established ML Estates"
description: "TensorFlow specialists cover serving, edge deployment and migration on established ML estates. Dedicated ML engineers for your product, managed by Azendo."
url: "https://azendo.co/skills/tensorflow/"
---

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3. TensorFlow

# TensorFlow specialists for your dedicated team.

TensorFlow is a machine learning framework with a mature production ecosystem: serving, mobile and browser runtimes, and pipeline tooling. It appears most often in estates where models have been in production for several years.

## Where TensorFlow fits in a long-term product team.

TensorFlow work is disproportionately maintenance of things that already run. A model trained four years ago, a serving setup left untouched since, and a version upgrade everyone has been deferring because the migration path is unclear. That is ordinary and it is where the value is.

Its deployment story remains a real strength. Serving at scale, running on mobile, and running in a browser are all better supported than in most alternatives, which is often why the estate is on TensorFlow and why moving off it is less attractive than it first appears.

## What your dedicated team does with TensorFlow.

Maintaining models somebody else trained is the normal condition of an established ML estate, and it rewards familiarity more than brilliance. A version upgrade deferred for two years is a week of work for whoever knows the estate and a month for whoever does not.

When new feature work sits on top of the existing models, companies [hire AI developers](https://azendo.co/services/dedicated-ai-engineering-team/) for it on the same agreement as the ML engineers who keep those models running.

## Common TensorFlow use cases.

* Upgrading a pinned version Moving off an old release with a tested path.
* Running models on device Deployment to mobile or edge where latency or privacy rules out a round trip.
* Retraining an ageing model Refreshing a model whose accuracy has drifted, with evaluation that proves the new one is better.

## Adding TensorFlow skills to your team.

Production model work sits with a [dedicated MLOps team](https://azendo.co/services/dedicated-mlops-team/), because the challenge is usually operational.

TensorFlow specialists join your team remotely as dedicated, full-time team members, selected, employed and managed by us in Chiang Mai and Bangkok. Companies that hire offshore developers through Azendo add the skill when the product calls for it.

## Roles that use TensorFlow

* [Computer Vision Engineer AI engineering](https://azendo.co/services/dedicated-ai-engineering-team/computer-vision-engineer/)
* [Machine Learning Engineer MLOps engineering](https://azendo.co/services/dedicated-mlops-team/machine-learning-engineer/)

## Service areas that use TensorFlow

* [AI engineering](https://azendo.co/services/dedicated-ai-engineering-team/)
* [MLOps engineering](https://azendo.co/services/dedicated-mlops-team/)

Capacity is agreed across your whole team, with one monthly fee, not per skill.

## Related in ai and machine learning

* [vLLM, a skill in our teams](https://azendo.co/skills/vllm/)
* [MLflow, a skill in our teams](https://azendo.co/skills/mlflow/)
* [Kubeflow, a skill in our teams](https://azendo.co/skills/kubeflow/)
* [OpenAI, a skill in our teams](https://azendo.co/skills/openai/)
* [Anthropic, a skill in our teams](https://azendo.co/skills/anthropic/)
* [Google Gemini, a skill in our teams](https://azendo.co/skills/google-gemini/)
* [Meta Llama, a skill in our teams](https://azendo.co/skills/meta-llama/)
* [Google and open-weight models, a skill in our teams](https://azendo.co/skills/google-and-open-weight-models/)

## Tell us what you need TensorFlow for.

A service delivery manager will reply with the specialists we'd suggest, the monthly capacity and what the first month looks like.

[Browse all skills](https://azendo.co/skills/)