AI Integration Specialist

3 days ago

Anand, Gujarat, India beBeeAIIntegration Full time ₹ 60,00,000 - ₹ 1,20,00,000

Our team seeks a talented AI Integration Specialist to join us in Ahmedabad.

This role involves deploying and integrating AI/ML models into production environments, ensuring scalability, reliability, and security.

You will collaborate with data scientists, software engineers, DevOps, and product teams to streamline AI adoption and ensure maximum impact from our AI-driven solutions.

The ideal candidate will have strong proficiency in Python and experience using FastAPI, Flask, or Django.

Additionally, they should have hands-on experience with Docker, Kubernetes, and container orchestration.

Familiarity with cloud platforms (AWS, GCP, Azure) and their AI/ML services is also desired.

This role requires excellent English communication skills – ability to work with cross-functional teams and present technical solutions clearly.

Key Responsibilities:

  1. Deploy and integrate AI models: Collaborate with AI/ML teams to deploy machine learning models into applications and services.

  2. Build APIs and microservices: Design and implement APIs, SDKs, and microservices that enable seamless AI model consumption.

  3. Ensure reliability: Maintain high availability, scalability, and security of AI services in production.

  4. Monitor and maintain models: Implement CI/CD pipelines, observability tools, and monitoring systems to track and improve model performance.

  5. Automate workflows: Build automated pipelines for model retraining, versioning, and rollback.

  6. Optimize performance: Implement caching strategies, model compression, and other techniques to improve inference speed and system efficiency.

  7. Cloud and hybrid infrastructure: Work with AWS, GCP, or Azure environments and support hybrid setups (cloud + on-prem).

Required Qualifications:

  1. Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

  2. 3–6 years of experience in software engineering, backend development, or MLOps.

  3. Strong proficiency in Python with experience using FastAPI, Flask, or Django.

  4. Experience integrating ML models with tools like TensorFlow Serving, TorchServe, ONNX, or custom model wrappers.

  5. Hands-on experience with Docker, Kubernetes, and container orchestration.

  6. Understanding of CI/CD pipelines, MLOps practices, and model lifecycle management.

  7. Familiarity with cloud platforms (AWS, GCP, Azure) and their AI/ML services.

  8. Excellent English communication skills – ability to work with cross-functional teams and present technical solutions clearly.

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