Embedded Machine Learning Engineer Jobs in Houston, TX

Job Description:

We are looking for an experienced Principal AI Engineer to drive the design, development, and deployment of AI/ML-powered applications. Candidate should have strong hands-on experience in application development, lead and mentor a team of AI developers, define best practices, and deliver scalable, production grade AI solutions aligned with business goals.

Location: Spring, Texas

Onsite daily work required

Key Responsibilities

• Design, develop, and deploy AI applications, microservices, and APIs on Kubernetes-based infrastructure, ensuring scalability, reliability, and performance across development, staging, and production environments.
• Build and maintain end-to-end AI pipelines covering deployment, monitoring, versioning, and continuous improvement using modern MLOps/AIOps tools and practices.
• Lead and mentor a team of AI/ML engineers, conduct code reviews, and define best practices.
• Continuously evaluate and adopt emerging AI tools, frameworks, LLM technologies, and open-source solutions to enhance platform capabilities and team productivity.
• Collaborate closely with Business Analysts, Architect and technical teams to align AI engineering efforts with business objectives and ensure secure, compliant solutions.
• Establish and maintain technical documentation, deployment runbooks and SOPs

Required Qualifications

• 10+ years of hands-on experience in software engineering, with a strong focus on AI/ML application development and deployment.
• Expertise in Kubernetes - container orchestration, Helm charts, pod management, scaling, and troubleshooting.
• Strong experience with MLOps/AIOps tools and practices (e.g., MLflow, Kubeflow, Airflow, model registries, monitoring frameworks).
• Hands-on experience with cloud platforms - Azure, AWS, or GCP, including their AI services.
• Strong programming skills in Python; familiarity with FastAPI, Flask, or similar frameworks is mandatory.
• Hands-on experience with CI/CD pipelines and tools such as GitOps, Docker, Jenkins, or GitHub Actions.
• Lead and mentor development teams, drive delivery, and manage technical priorities.
• Experience working with Agentic and GenAI frameworks and vector databases etc.
• Experience with observability and monitoring tools (Prometheus, Grafana, OpenTelemetry) for AI workloads.
• Good understanding of AI security, responsible AI principles, and governance frameworks.

Education

• Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, or a related field.

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