HOUSTON ML ENGINEERING
From a working model to a dependable production system
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Machine learning engineering services in Houston from DESSS focus on the part of machine learning that comes after the model is trained. We package models, build training and deployment pipelines, set up monitoring and design retraining so predictions stay accurate as the data changes.
Data scientists are good at finding patterns. Running a model as a service is a different job: it needs versioned data and code, automated testing, secure APIs, logging, cost control and a plan for when the model starts to drift. That engineering work is what we provide.
If you are still deciding which problems machine learning should solve, start with our machine learning services in Houston or data science services in Houston. This page covers the engineering that puts those models into production.
When to call us
When a model works in testing but has no path to production, or a live model needs monitoring and retraining.
What you receive
Automated pipelines, a deployed and versioned model, monitoring dashboards and runbooks.
Who it is for
Data science teams, engineering leaders and operations groups that rely on model predictions.
Where we work
From our Houston headquarters, with an office in Austin, for clients across Texas.
OUR SERVICES
Machine learning engineering services in Houston
These six services cover the engineering a model needs to run in production. You can engage us for one of them or all six.
MLOps pipeline development
Automated pipelines for data preparation, training, evaluation and model registration, run on a schedule or when new data arrives.
Production ML model deployment
Models packaged in containers and served through real-time APIs or batch jobs, with staged releases and rollback.
ML model monitoring and retraining
Tracking of prediction quality, data drift, latency and cost, with alerts and retraining when performance drops.
Feature and data pipelines
Reliable, versioned input data so the features used in training match the features used in production.
Model performance and cost tuning
Faster inference, right-sized compute and lower cloud spend without losing accuracy.
Dedicated ML engineers
Engineers who work inside your team on your backlog, alongside your data scientists and developers.
COMMON PROJECTS
MLOps services in Houston, project by project
The projects Houston teams bring to us most often, and how we handle each one.
MLOps services in Houston
How do we stop retraining by hand? Our MLOps services in Houston replace manual steps with automated, repeatable pipelines. We version data, code and models, track experiments in tools such as MLflow, add automated tests for data and model quality, and connect training to CI/CD so a new model version goes through the same checks every time.
–Experiment tracking and model registry
–Data and model validation tests
–CI/CD for models
–Scheduled or event-driven training
ML model deployment services in Houston
How do we put the model into production? Our ML model deployment services in Houston package models in containers and serve them as real-time APIs, batch scoring jobs or embedded components, depending on how the predictions are used. We deploy on Amazon SageMaker, Azure Machine Learning, Google Vertex AI or Kubernetes, with staged or shadow releases so a new model is proven before it replaces the old one.
Applications that consume the model can be built by our AI development team.
–Real-time and batch serving
–Shadow and staged releases
–Rollback to a previous version
–Security and access control
ML model monitoring and retraining
How do we know the model still works? Models lose accuracy when the data they see changes. We monitor input data drift, prediction distributions, accuracy against actual outcomes where those are available, latency and cost. Alerts go to the right people, and retraining can run on a schedule or when a threshold is crossed, with a person approving the release where the risk calls for it.
–Data and prediction drift checks
–Accuracy tracking against outcomes
–Latency and cost dashboards
–Approved retraining workflow
Machine learning for oil and gas companies in Houston
Where does ML fit in energy operations? Machine learning for oil and gas companies in Houston often works with sensor and operational data. Typical use cases include predictive maintenance for pumps and compressors, production forecasting, anomaly detection on pipelines and equipment, and support for interpreting drilling and well data. These models need dependable pipelines from historians and field systems, and monitoring that accounts for changing operating conditions.
–Predictive maintenance
–Production forecasting
–Equipment and pipeline anomaly detection
–Sensor and historian data pipelines
Hire ML engineers in Houston
Can we add engineers to our own team? If you want to hire ML engineers in Houston without a long recruiting process, DESSS can provide dedicated ML engineers who work on your backlog under your direction, on site in Houston or remotely. Companies looking for a machine learning development company in Houston, TX can also hand us a full project, from pipeline design to production support.
–Python, cloud ML and MLOps skills
–On-site or remote
–Project or dedicated engagement
–Handover documentation
HOW WE WORK
How an ML engineering engagement runs
Our machine learning engineering services follow six steps, whether we are deploying one model or building a shared MLOps platform.
STEP 01
Review
We review the model, its data, how predictions will be used and the platform you run on.
STEP 02
Design
We design the MLOps pipeline development approach, the serving pattern and the monitoring plan.
STEP 03
Build pipelines
Data, training and evaluation pipelines are automated, versioned and tested.
STEP 04
Deploy
Production ML model deployment with staged release, security controls and rollback.
STEP 05
Monitor
Drift, accuracy, latency and cost are tracked, with alerts and dashboards.
STEP 06
Retrain and support
Retraining is set up and documented, and we can stay on for ongoing support.
RELATED SERVICES
Services that work alongside ML engineering
A production model depends on good data, sound modeling and applications that use it. DESSS can help with each.
WHY DESSS
Why choose DESSS as your machine learning development company in Houston, TX
Production ML is mostly engineering. We bring software, data and cloud skills to the model your team built.
Software engineering habits
Version control, automated tests, code review and CI/CD apply to models as well as applications.
Data platform experience
We also build data warehouses and pipelines, so model inputs are reliable at the source.
No lock-in
Pipelines and infrastructure are documented and handed over so your team can run them.
Local to Houston
Design workshops and launch support can happen in person at your office or ours.
DESSS machine learning engineering services include MLOps pipeline development, production ML model deployment, ML model monitoring and retraining, feature and data pipelines, performance and cost tuning, and dedicated ML engineers.
Data science focuses on exploring data and building models. Machine learning engineering focuses on running those models reliably in production: pipelines, deployment, monitoring, retraining and infrastructure. Most successful projects need both.
MLOps applies DevOps practices to machine learning. It covers versioning of data, code and models, automated training and testing, controlled deployment and ongoing monitoring, so models can be updated safely and often.
We deploy on Amazon SageMaker, Azure Machine Learning, Google Vertex AI, Databricks and Kubernetes, using tools such as MLflow, Docker and FastAPI. We usually build on the cloud platform you already use.
Yes. You can hire dedicated ML engineers from DESSS who work on your backlog, follow your standards and work on site in Houston or remotely.
We monitor data drift, prediction quality, latency and cost, and set alerts for each. Retraining runs on a schedule or when performance drops, and new versions are tested before they replace the live model.
HOUSTON ML ENGINEERING
Talk to us about machine learning engineering services in Houston
Book a short call about machine learning engineering services in Houston. Tell us about your models, your data and where they need to run, and we will outline a practical path to production.
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