Senior Machine Learning Engineer

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AI Summary

Design, build, and productionize AI and machine learning solutions using Azure services and cloud-native architectures. Partner with product, data science, and platform teams. Strong experience with Azure, Python, and agile development practices.

Key Highlights
Machine Learning Engineer position available on a W2 contract
9+ month contract in Houston, TX
75-110 an hour pay range
Key Responsibilities
Design and implement cloud-native AI architectures using Microsoft Azure services
Collaborate with Data Scientists and other AI Engineers to transform prototypes into production-ready solutions
Build, deploy, and operate enterprise-scale machine learning pipelines emphasizing reliability, performance, and security
Technical Skills Required
Microsoft Azure Python Ansible Docker Kubernetes Azure Machine Learning
Benefits & Perks
Contract opportunity with W2 payment only
Visa sponsorship available
Location - Houston, TX with 4 days on-site, 1 day remote
Nice to Have
Experience implementing or operating agentic AI systems
Familiarity with data engineering tools such as Databricks, Spark, Azure Data Factory

Job Description


STRATEGIC STAFFING SOLUTIONS HAS AN OPENING!

This is a Contract Opportunity with our company that MUST be worked on a W2 Only. No C2C eligibility for this position. Visa Sponsorship is Available! The details are below.

“Beware of scams. S3 never asks for money during its onboarding process.”


Job Title: Machine Learning Engineer

Contract Length: 9+ Month contract

Location: Houston, TX 77002 (4 days on site/ 1 day remote)

Pay: 75-110 an hr on W2


We are seeking an experienced AI Engineer to partner with product, data science, and platform teams to design, build, and productionize AI and machine learning solutions. This role is delivery-focused and hands-on, emphasizing cloud architecture, MLOps, automation, and operational excellence.

The ideal contractor brings strong Azure experience, a software engineering mindset, and practical experience operationalizing AI systems at scale. Experience with Microsoft Foundry is strongly preferred.

Key Responsibilities

  • Partner with business and technical stakeholders to identify and implement agentic AI and machine learning solutions that improve decision-making, workflows, and automation.
  • Design and implement cloud-native AI architectures using Microsoft Azure services and established AI design patterns.
  • Collaborate with Data Scientists and other AI Engineers to transform prototypes into production-ready, scalable solutions.
  • Build, deploy, and operate enterprise-scale machine learning pipelines emphasizing reliability, performance, and security.
  • Orchestrate and configure infrastructure that enables low-latency, resilient AI workloads using infrastructure-as-code and automation.
  • Contribute to reusable accelerators, templates, and patterns that improve delivery speed and consistency across teams.
  • Support CI/CD, monitoring, and operational practices for AI and ML systems in production environments.

Required Technical Skills

  • Strong experience with Microsoft Azure, including AI/ML services and cloud-native architectures.
  • Hands-on experience deploying and operating ML pipelines using Azure Machine Learning.
  • Proficiency in Python and modern software engineering practices.
  • Experience with automation and configuration management, including Ansible.
  • Solid understanding of MLOps, model lifecycle management, and CI/CD for AI systems.
  • Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).
  • Working knowledge of security, identity, and access control in enterprise cloud environments.

Preferred Skills

  • Experience with Microsoft Foundry.
  • Experience implementing or operating agentic AI systems.
  • Familiarity with data engineering tools such as Databricks, Spark, Azure Data Factory.
  • Experience integrating AI services (e.g., cognitive services, computer vision, unstructured data processing).

Experience Requirements

  • 5+ years of experience in software engineering, AI engineering, or machine learning engineering roles.
  • Proven experience delivering production AI or ML solutions in a cloud environment.
  • Experience collaborating with cross-functional teams across data science, engineering, and architecture.

Ways of Working

  • Ability to work independently as a contractor while integrating effectively with existing teams.
  • Strong communication skills with the ability to explain complex technical concepts clearly.
  • Results-oriented mindset focused on delivering business value quickly and reliably.


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