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SeniorRemote

Machine Learning Engineer

TA
Tiger Analytics Inc.
Уровень
Senior
Формат
Remote
О роли

Описание вакансии

About the company

Tiger Analytics is looking for a skilled and innovative Machine Learning Engineer with hands-on experience in Google Cloud Platform (GCP) and Vertex AI to design, build, and deploy scalable ML solutions. You will play a key role in operationalizing machine learning models and driving the end-to-end ML lifecycle, from data ingestion to model serving and monitoring.

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
Requirements
  • Advanced Generative AI: Advanced RAG including Graph based hybrid retrieval, Multimodal agent
  • Deep knowledge on ADK, Langchain Agentic Frameworks
  • Fine tuning and Distillation
  • Expert in Python with strong OOP and functional programming skills
  • Proficient in ML/DL libraries: TensorFlow, PyTorch, scikit-learn, pandas, NumPy, PySpark
  • Experience with production-grade code, testing, and performance optimization
  • Proficiency in GCP services: Vertex AI, BigQuery, Cloud Storage, Cloud Run, Cloud Functions, Pub/Sub, Dataproc, Dataflow
  • Understanding of IAM, VPC
  • Designs and builds RESTful APIs using FastAPI or Flask
  • Integrates ML models into APIs for real-time inference
  • Implements authentication, logging, and performance optimization
  • Designs end-to-end AI systems with scalability and fault tolerance in mind
  • Hands-on experience in developing distributed systems, microservices, and asynchronous processing
Conditions
  • Significant career development opportunities exist as the company grows
  • The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility
Стек и навыки

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