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Machine Learning Engineer (Ops)
Accrete.ai
Machine Learning Engineer (Ops)
Accrete.ai's logo

Machine Learning Engineer (Ops)

at Accrete.ai

5 - 14 yrs
₹50L - ₹70L / yr
Mumbai
Skills
skill iconMachine Learning (ML)
skill iconData Science
Natural Language Processing (NLP)
Computer Vision
kubeflow
Data Structures
skill iconDocker
skill iconKubernetes
PyTorch
TensorFlow
Keras
skill iconAmazon Web Services (AWS)
MLOps

Responsibilities:

  • Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality.
  • Design and implement cloud solutions, build MLOps on the cloud (preferably AWS)
  • Work with workflow orchestration tools like Kubeflow, Airflow, Argo, or similar tools
  • Data science models testing, validation, and test automation.
  • Communicate with a team of data scientists, data engineers, and architects, and document the processes.


Eligibility:

  • Rich hands-on experience in writing object-oriented code using python
  • Min 3 years of MLOps experience (Including model versioning, model and data lineage, monitoring, model hosting and deployment, scalability, orchestration, continuous learning, and Automated pipelines)
  • Understanding of Data Structures, Data Systems, and software architecture
  • Experience in using MLOps frameworks like Kubeflow, MLFlow, and Airflow Pipelines for building, deploying, and managing multi-step ML workflows based on Docker containers and Kubernetes.
  • Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc. )
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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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Shubham Vishwakarma

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