AI Deployment Specialist

5 days ago

Ajmer, Rajasthan, India beBeeIntegration Full time ₹ 15,00,000 - ₹ 25,00,000
Job Title: AI Integration Engineer

This role involves deploying and integrating AI/ML models into production environments to drive business value.

Main Responsibilities:

  • Deploy and Integrate AI Models: Collaborate with AI/ML teams to deploy machine learning models into applications and services, ensuring seamless integration and efficient model deployment.
  • Build APIs and Microservices: Design and implement APIs, SDKs, and microservices that enable the consumption of AI models by various applications and services.
  • Maintain High Availability and Scalability: Ensure high availability, scalability, and security of AI services in production environments.
  • Monitor & Maintain Models: Implement CI/CD pipelines, observability tools, and monitoring systems to track and improve model performance.
  • Automate Workflows: Build automated pipelines for model retraining, versioning, and rollback, minimizing manual intervention and maximizing efficiency.
  • Optimize Performance: Implement caching strategies, model compression, and other techniques to improve inference speed and system efficiency.
  • Cloud & Hybrid Infrastructure: Work with cloud platforms (AWS, GCP, Azure) and support hybrid setups (cloud + on-prem), ensuring smooth integration and scalability.
  • Cross-Functional Collaboration: Partner with DevOps, software engineers, and product teams to integrate AI capabilities smoothly into products and services, driving business outcomes.

Required Qualifications:

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • 3 – 6 years of experience in software engineering, backend development, or MLOps, with a strong focus on AI/ML model deployment and integration.
  • Strong proficiency in Python with experience using FastAPI, Flask, or Django, as well as hands-on experience with Docker, Kubernetes, and container orchestration.
  • Experience integrating ML models with tools like TensorFlow Serving, TorchServe, ONNX, or custom model wrappers.
  • Understanding of CI/CD pipelines, MLOps practices, and model lifecycle management, with excellent problem-solving skills and attention to detail.
  • Familiarity with cloud platforms (AWS, GCP, Azure) and their AI/ML services, with a strong understanding of scalability, security, and compliance.
  • Excellent English communication skills, with the ability to work effectively with cross-functional teams and present technical solutions clearly and persuasively.

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