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    Embitel Technologies logo

    Machine Learning Engineer (Computer Vision)

    Embitel Technologies · Bengaluru · onsite · Posted 1d ago

    Undisclosed3–8 yrsfulltimeSourced fromNaukri

    About a minute. You'll make an account on the way through.

    About this role

    Job Summary

    Job Description - Machine Learning Engineer (Computer Vision)

    About the role

    We are hiring a Machine Learning Engineer with 3+ years of hands-on experience to build, deploy and operate AI and computer vision systems on Microsoft Azure. You will own models end to end: from data pipelines and training to production deployment, monitoring and retraining.

    Role: Machine Learning Engineer

    Experience: 3 to 5 Years

    Cloud: Microsoft Azure

    Location: Bangalore / Hybrid

    Type: Full-time

    Key responsibilities

    • AI and computer vision: Design, train and fine-tune models for image classification, object detection, segmentation and OCR
    • Build image and video processing pipelines with OpenCV, including augmentation workflows.
    • Explore and integrate generative AI where it fits, such as Azure OpenAI and vision-language models.

    Data engineering

    • Build batch and streaming pipelines with Azure Data Factory, Azure Databricks and PySpark.
    • Manage data in Azure Data Lake Storage and Blob Storage, including large image and video datasets.
    • Ensure data quality, versioning and lineage for training and evaluation datasets.

    MLOps on Azure

    • Run experiments, model registry and deployments in Azure Machine Learning (pipelines, managed online and batch endpoints).
    • Build CI/CD for models and pipelines with Azure DevOps or GitHub Actions.
    • Containerize services with Docker and deploy to Azure Kubernetes Service (AKS) or Azure Container Apps.
    • Monitor models in production for drift, accuracy and latency with Azure Monitor and Application Insights, and automate retraining.
    • Manage infrastructure as code with Terraform

    Collaboration

    • Work with data scientists, product owners and software engineers to turn business problems into ML solutions.
    • Write clear documentation and take part in code reviews.

    Required qualifications

    • Bachelors or Masters degree in Computer Science, Data Science, AI, Electrical Engineering or a related field.
    • 3+ years of professional experience in machine learning engineering, with at least 2 years on computer vision projects.
    • At least one computer vision model taken from prototype to production and maintained there.
    • 2+ years working with Microsoft Azure data and ML services.
    • Strong Python and solid software engineering habits: testing, version control, clean code.
    • Good grasp of ML fundamentals: model evaluation, feature engineering, and deep learning architectures.
    • Clear communication with both technical and non-technical stakeholders.

    Nice to have

    • Microsoft certifications: Azure Data Scientist Associate (DP-100)
    • Experience with AgenticAI, RAG.


    Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

    Sourced from naukri

    Skills

    data qualityPrototypeAutomotiveComputer VisionGermanMonitoringPythonComputer ScienceMicrosoftMachine Learning

    About Embitel Technologies

    Embitel Technologies logo

    Embitel Technologies

    IT Services & Consulting

    1.4k+

    employees

    2006

    20 years old

    Bangalore / Bengaluru, Karnataka

    India

    About

    Embitel offers- Product engineering services (Automotive & Connected Cars), IoT for Industry 4.0, eCommerce website development and digital experience-driven solutions

    Industries

    IT Services & ConsultingHardware & Networking

    Employee ratings

    286 reviews

    4.0/ 5

    Culture

    4.0

    Career growth

    3.5

    Work-life

    4.2

    Employees rate it well for

    Work Life Balance30Senior Management20Work Culture16Salary15Work Environment14

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