Machine Learning Engineer - Hyderabad - Kresta Softech Private Limited

    Kresta Softech Private Limited
    Technology / Internet
    Description

    ML Engineer

    Experience-5+ Years

    Immediate Joiners Only

    Location : Hyderabad

    Job Description:

    We are seeking an experienced Machine Learning Engineer to design, build, deploy, and maintain scalable ML systems in a production environment. This role involves close collaboration with data scientists, ownership of ML pipelines, and hands-on work with Google Cloud Platform. The ideal candidate will have strong experience in MLOps, production deployments, monitoring, and ML systems reliability.

    Key Responsibilities:

    · Build and maintain reliable data pipelines

    · Prepare clean, structured datasets for machine learning

    · Work with data from client's data warehouse and other internal sources

    · Use transformation tools like dbt when needed

    · Automate ML training workflows on Google Cloud Platform

    · Build reproducible ML pipelines

    · Work with data scientists to turn experimental models into production-ready systems

    · Deployment & Serving

    · Deploy ML models using Cloud Run, Kubernetes, and Vertex AI

    · Build and maintain REST APIs in Python to serve predictions

    · Ensure models are fast, stable, and secure

    · Set up dashboards with DataDog, Grafana, or similar tools

    · Monitor model performance, accuracy, data drift, and system health

    · Troubleshoot issues and ensure smooth operation in production

    Required Skills and Qualifications:

    · 5+ years of experience building and deploying ML models in production

    · Strong Python skills (pipelines, training workflows, APIs)

    · Experience with ML frameworks (TensorFlow, PyTorch, scikit-learn, etc.)

    · Solid understanding of MLOps practices: CI/CD, model versioning, automated pipelines, monitoring

    · Hands-on experience with GCP services: Cloud Run, Kubernetes, BigQuery, Vertex AI

    · Experience building APIs (FastAPI, Flask, or similar)

    · Good understanding of automated testing · Monitoring: Experience with DataDog or Grafana · Knowledge of ethical AI, bias mitigation, or data privacy principles · Knowledge of AI guardrailing · Experience with recommender systems · Vector databases · Embeddings · Feature engineering · Matrix factorization techniques · Ttwin tower models · Basic experience or exposure to recommender systems · Monitoring and observability of models in production · User feedback handling · Model training and evaluation (at least theoretical understanding) · A/B testing · Performance metrics


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