AI Model Deployment Specialist

1 day ago

Noida, Uttar Pradesh, India beBeeMachineLearningEngineer Full time ₹ 20,00,000 - ₹ 25,00,000

Key Position: Senior Machine Learning Engineer

Job Description

We are seeking an experienced Senior Machine Learning Engineer to oversee the development and deployment of our machine learning models. The ideal candidate will have strong knowledge of the ML lifecycle, hands-on experience with MLflow, Docker, and Kubernetes, as well as proficiency in CI/CD pipelines using tools like GitHub Actions.

This role involves designing and managing end-to-end ML pipelines, automating stages from data ingestion and model training to deployment and monitoring. You will also own and maintain CI/CD pipelines for deep learning models across multiple deployment targets, including Android, iOS, Web, and On-premises / edge devices.

The successful candidate will leverage their expertise to integrate and manage MLflow for tracking experiments, versioning models, and managing deployments. They will also orchestrate workflows using Apache Airflow to ensure reliable, scheduled, and maintainable model lifecycle operations.

Required Skills and Qualifications
  • Strong understanding of ML lifecycle and experience managing training-to-deployment pipelines.
  • Hands-on experience with MLflow for model tracking and optimization.
  • Proficient with Docker and container orchestration tools such as Kubernetes.
  • Experience with CI/CD pipelines using tools like GitHub Actions, GitLab CI, or similar.
  • Familiarity with TensorRT, ONNX, and model optimization for edge and embedded systems.
  • Proven track record of deploying models on TFLite, CoreML, and WebAssembly platforms.
  • Experience with workflow orchestration using Apache Airflow or similar tools.
  • Exposure to monitoring tools like Prometheus, Grafana, Seldon, or WhyLabs.
Benefits

You will be part of a fast-paced environment where you can showcase your skills and creativity. As a Senior Machine Learning Engineer, you will have the opportunity to work closely with data scientists, ML engineers, and product teams to ensure robust and efficient deployment.

Others

The ideal candidate will possess excellent problem-solving skills, attention to detail, and strong communication and documentation skills. They should be able to work collaboratively in cross-functional teams and continuously improve deployment latency, inference throughput, and edge-device performance.

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