Role overview

Senior Machine Learning Engineer (GCP)

Requirements and responsibilities

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Key Responsibilities:

  • Develop, train, and optimize ML models using Vertex AI, including Vertex Pipelines, AutoML, and custom model training.
  • Design and build scalable ML pipelines for feature engineering, training, evaluation, and deployment.
  • Deploy models to production using Vertex AI endpoints and integrate with downstream applications or APIs.
  • Collaborate with data scientists, data engineers, and MLOps teams to enable reproducible and reliable ML workflows.
  • Monitor model performance and set up alerting, retraining triggers, and drift detection mechanisms.
  • Utilize GCP services such as BigQuery, Dataflow, Cloud Functions, Pub/Sub, and GCS in ML workflows.
  • Apply CI/CD principles to ML models using Vertex AI Pipelines, Cloud Build, and GitOps practices.
  • Implement model governance, versioning, explainability, and security best practices within Vertex AI.
  • Document architecture decisions, workflows, and model lifecycle clearly for internal stakeholders.

- Multimodal agent

  • Deep knowledge on ADK , Langchain Agentic Frameworks
  • Fine tuning and Distillation
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Browse stack
FocusMachine Learning EngineerRole area
Seniority signalSeniorCandidate level
StackCI/CD, GCP, PythonPrimary skills
Location1 accepted countryEligibility

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