Machine Learning Engineer (with Vertex AI Experience)
Tiger Analytics Inc.10 months ago
Remote, CanadaSenior
Responsibilities
- Develop, train, optimize, and deploy ML models using Vertex AI, Vertex Pipelines, AutoML, and custom model training.
- Design scalable ML pipelines for feature engineering, training, evaluation, deployment, and reproducible ML workflows.
- Deploy models to Vertex AI endpoints and integrate them with downstream applications and APIs for real-time inference.
- Build advanced generative AI systems with graph-based hybrid RAG, multimodal agents, agentic frameworks, fine-tuning, and distillation.
- Use GCP services including BigQuery, Dataflow, Cloud Functions, Pub/Sub, GCS, Cloud Run, Dataproc, and Cloud Storage in ML workflows.
- Monitor model performance and implement alerting, retraining triggers, and drift detection.
- Implement model governance, versioning, explainability, security, and reliable ML lifecycle practices.
- Design and build RESTful APIs with FastAPI or Flask, including authentication, logging, and performance optimization.
- Document architecture decisions, workflows, and model lifecycle processes for internal stakeholders.
Requirements
- Advanced experience with RAG, including graph-based hybrid retrieval, multimodal agents, ADK, and LangChain agentic frameworks.
- Experience with fine-tuning and distillation.
- Expert Python skills with strong object-oriented and functional programming capabilities.
- Proficiency with TensorFlow, PyTorch, scikit-learn, pandas, NumPy, and PySpark.
- Production-grade coding, testing, and performance optimization experience.
- Proficiency with GCP services including Vertex AI, BigQuery, Cloud Storage, Cloud Run, Cloud Functions, Pub/Sub, Dataproc, Dataflow, IAM, and VPC.
- Experience designing and building APIs with FastAPI or Flask and integrating ML models for real-time inference.
- Experience designing scalable, fault-tolerant AI systems and developing distributed systems and asynchronous processing.
Benefits
- Remote work arrangement.
- Significant career development opportunities in a small, fast-growing, challenging, and entrepreneurial environment.
- High degree of individual responsibility.
Tech Stack
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