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GenAI Architect

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Full Remote
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Offer summary

Qualifications:

Strong hands-on experience with AI/ML models, Extensive experience with embedded Linux and IoT, Proficiency in cloud platforms (AWS, Azure, GCP), Advanced programming skills in multiple languages.

Key responsabilities:

  • Lead architecture for AI-driven solutions
  • Deploy and maintain MLOps workflows and automation
Zealogics Inc logo
Zealogics Inc Information Technology & Services SME https://www.zealogics.com/
501 - 1000 Employees
See more Zealogics Inc offers

Job description

  • AI and GenAI Solution Design:
    • Lead architecture and development of AI-driven solutions using tools such as Azure OpenAI, NVIDIA NGC, Google Vertex AI, and AWS Bedrock/SageMaker.
    • Integrate and customize pre-trained models from OpenAI, Llama3, NVIDIA, and other platforms, optimizing for specific use cases (e.g., customer service, data analytics).
    • Implement and manage GenAI services, leveraging Task Weaver, Google Vertex AutoML, and local LLMs for tailored AI applications.
  • MLOps and Data Pipeline Automation:
    • Deploy and maintain MLOps workflows using tools like Kubeflow, MLFlow, and CI/CD practices for data lakes with LakeFS.
    • Architect and maintain multi-cloud data pipelines and storage solutions with Kubernetes, K3s/K8s, and Docker.
  • Embedded Linux and IoT Solutions:
    • Design and develop custom embedded Linux solutions for devices such as Beaglebone, Raspberry Pi, and OrangePi using Yocto, Armbian, and BuildRoot.
    • Integrate and deploy IoT edge solutions on microcontrollers like ESP32/ESP8266, RP2040, with a focus on advanced protocols and device management.
    • Deploy, configure, and manage edge computing devices, including NVIDIA Jetson, ZimaBoard, and Raspberry Pi, leveraging AI capabilities for IoT applications.
  • Cloud Architecture and Edge Integration:
    • Architect scalable multi-cloud solutions on AWS, Azure, and Google Cloud for AI, data, and IoT workloads.
    • Implement edge streaming, digital twin creation, and IoT device management using Azure IoT Hub, Google IoT Core, and AWS IoT Core.
    • Enable cross-platform integration with observability tools, data analytics, and cloud database solutions (Cosmos DB, BigQuery, Snowflake).
  • DevOps and Automation:
    • Develop multi-cloud and on-premise automation solutions using tools like Terraform, Helm, and CDK/TypeScript for infrastructure-as-code.
    • Optimize DevOps workflows and automate processes with CI/CD pipelines, monitoring solutions, and advanced configurations across cloud platforms.

  • Expertise:
    • Strong hands-on experience with AI/ML models and platforms (e.g., OpenAI).
    • Proven track record in MLOps, using tools like Kubeflow, MLFlow, and LakeFS.
    • Extensive experience with embedded Linux, IoT device management, and edge computing.
    • Proficiency in cloud platforms (AWS, Azure, GCP), IoT architecture, blockchain, and advanced DevOps.
    • Advanced programming skills in Python, C++, Go, JavaScript, Bash, and PowerShell.
  •  

Required profile

Experience

Industry :
Information Technology & Services
Spoken language(s):
English
Check out the description to know which languages are mandatory.

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