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2 results for Rpa Engineer in Dallas, TX
- Dallas, TX
- onsite
- Temporary to Hire
- 75 - 83 USD / Hourly
- <p>I’m working with a Healthcare technology organization seeking a Senior Cloud Security Engineer to design, automate, and operate cloud security controls within a Microsoft Azure environment. This role will focus on cloud security engineering, automated remediation, identity security, DevSecOps integration, and compliance within a highly regulated environment.</p><p> </p><p><strong>POSITION: AZURE CLOUD SECURITY </strong></p><p><strong>LOCATION: DALLAS, 75201 (HYBRID 3 DAYS ONSITE)</strong></p><p><strong>DURATION: 6 MONTH CONTRACT TO PERMANENT</strong></p><p><strong>SALARY: 155K – 170K DEPENDING ON EXPERIENCE</strong> </p><p> </p><p><strong>RESPONSIBILITIES</strong></p><ul><li>Engineer and support cloud security platforms including Wiz, Microsoft Defender for Cloud, and related Azure security technologies.</li><li>Design automation workflows that move security findings from detection through remediation using APIs, scripting, and event-driven architectures.</li><li>Implement policy-as-code, Infrastructure-as-Code security controls, Azure Policy, and CI/CD security guardrails.</li><li>Secure Azure identity and network environments including Microsoft Entra ID, Conditional Access, PIM, Azure Firewall, NSGs, and Fortinet solutions.</li><li>Partner with DevOps, SRE, and infrastructure teams to improve cloud security posture, incident response capabilities, and compliance readiness.</li></ul><p><br></p>
- 2026-10-29T00:00:00Z
- Coppell, TX
- onsite
- Temporary / Contract
- 75 - 80 USD / Hourly
- <p>We are looking for a MLOps Engineer II w/ a focus on GPU Compute to join a team in Coppell, Texas, on a Long-term Contract assignment. In this role, you will design and refine vision-based AI solutions that support real-world image and video use cases, while partnering with cross-functional teams to move ideas from research into production. The position is ideal for someone who combines strong machine learning expertise with practical understanding of hardware constraints and model performance in live environments.</p><p><br></p><p><strong>Responsibilities:</strong></p><p>•Deploy GPUs (Graphics Processing Units) workflows in a retail environment that requires processing massive amounts of image, video, customer, and transaction data.</p><p>•Design, build, and enhance computer vision and machine learning models for use cases involving object detection, image segmentation, classification, and video-based analysis.</p><p>•Compare modeling approaches, assess trade-offs across accuracy, speed, and scalability, and recommend fit-for-purpose solutions aligned with business goals.</p><p>•Train and adapt deep learning models using frameworks such as PyTorch or TensorFlow, applying techniques like transfer learning and optimization for efficient performance.</p><p>•Establish evaluation methods, track key performance measures, investigate error patterns, and iterate on models to improve reliability and response time.</p><p>•Incorporate practical considerations related to cameras, sensors, lighting conditions, and edge hardware when developing and tuning solutions.</p><p>•Create and support data preparation, annotation, and validation workflows that enable consistent experimentation and dependable deployment.</p><p>•Work closely with software, hardware, and MLOps partners to transition models from proof of concept into production-ready applications.</p><p>•Contribute to deployment readiness by helping optimize models for inference and operational use in resource-constrained environments.</p>
- 2026-10-27T00:00:00Z