Senior AI/ML Engineer

Position Overview:

Senior AI/ML Engineer

Key Responsibilities:

• Design, develop, and deploy machine learning models at scale using

  Vertex AI, AI Platform, TensorFlow, PyTorch, or Scikit-learn

  .
• Build and maintain

  end-to-end ML pipelines

  including data preprocessing, feature engineering, model training, validation, deployment, and monitoring.
• Collaborate with

  data engineers

  to integrate high-quality data sources from

  BigQuery, Dataplex, and Dataflow

  into ML workflows.
• Implement

  MLOps best practices

  for versioning, reproducibility, CI/CD for ML, and automated model retraining.
• Optimize models for

  latency, scalability, and cost-efficiency

  in production environments.
• Leverage

  Vertex AI pipelines, Feature Store, and Model Monitoring

  to manage the ML lifecycle.
• Collaborate with business stakeholders and data scientists to translate requirements into AI/ML solutions that drive measurable impact.
• Explore cutting-edge AI techniques (e.g., NLP, computer vision, recommendation systems, generative AI) to prototype and deliver innovative solutions.
• Document architectures, workflows, and operational processes to ensure scalability and maintainability.

Required Skills:

• Minimum of 10 years of overall experience, with at least 3 years in

  AI/ML engineering

  .
• Strong hands-on experience with

  Google Cloud AI/ML services

  , including

  Vertex AI, BigQuery ML, AI Platform, and Dataplex

  .
• Expertise in

  Python

  (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch).
• Deep understanding of

  machine learning algorithms

  (supervised, unsupervised, deep learning, reinforcement learning).
• Experience deploying ML models as APIs or microservices using

  Cloud Run, Cloud Functions, or Kubernetes (GKE)

  .
• Familiarity with

  feature engineering, data pipelines, and data governance

  in GCP.
• Experience with

  MLOps frameworks

  (Kubeflow, MLflow, TFX) and CI/CD integration.
• Strong knowledge of

  SQL

  and working with data warehouses such as

  BigQuery

  .
• Familiarity with

  real-time/streaming data

  (Pub/Sub, Kafka).

Preferred Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, or related field (or equivalent experience).

• Google Cloud Professional Machine Learning Engineer Certification

  strongly preferred.
• Experience with

  NLP frameworks

  (e.g., Hugging Face Transformers, spaCy) or

  computer vision libraries

  (e.g., OpenCV, Detectron2).
• Exposure to

  Generative AI/LLM-based solutions

  and integration with GCP’s

  Generative AI Studio

  is a plus.
• Experience with

  AutoML

  and low-code/no-code ML development on GCP.