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Information Technology 🏢 Full Time ⭐️ Verified

AI/ML Solutions Architect

Nexus Analytics
Austin
Estimated Salary
USD 180.000 – USD 280.000
Live Update
11 Mei 2026
Deadline
11 Mei 2027

Job Description

Join Nexus Analytics as we pioneer the next wave of AI-driven solutions for 2026 and beyond. We're seeking an AI/ML Solutions Architect to design and implement cutting-edge machine learning systems that will redefine industry standards. You'll work in our state-of-the-art Austin hub, collaborating with world-class data scientists and engineers to transform complex business challenges into scalable AI solutions. Our culture thrives on innovation, continuous learning, and pushing the boundaries of what's possible in artificial intelligence.

Responsibilities

  • Design and implement end-to-end ML pipelines for predictive analytics and automation
  • Architect cloud-native AI solutions on AWS/GCP with emphasis on scalability and security
  • Lead technical workshops to translate business requirements into ML roadmaps
  • Optimize model performance through advanced feature engineering and hyperparameter tuning
  • Stay ahead of emerging AI trends including generative AI and quantum computing applications
  • Mentor junior engineers on best practices in MLOps and responsible AI
  • Collaborate with product teams to integrate ML solutions into customer-facing platforms

Qualifications

  • 5+ years in AI/ML architecture with proven portfolio of production systems
  • Expertise in Python, TensorFlow, PyTorch, and cloud ML services (SageMaker, Vertex AI)
  • Strong background in distributed computing and containerization (Docker, Kubernetes)
  • Experience with MLOps tools (MLflow, Kubeflow) and CI/CD pipelines
  • Advanced knowledge of statistical modeling and experimental design
  • PhD or Master's in Computer Science, Mathematics, or related field
  • Certification in AWS/GCP ML architecture preferred
  • Demonstrated ability to lead cross-functional technical initiatives

Required Skills

Python TensorFlow PyTorch AWS GCP Kubernetes MLOps Machine Learning AI Architecture Distributed Systems

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