We are redirecting you to the source. If you are not redirected in 3 seconds, please click here.

Senior Machine Learning Engineer (GCP) at Tiger Analytics. Location Information: Canada - Remote. . 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.. . 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. . . . Requirements. 1. Advanced Generative AI. - Advanced RAG including Graph based hybrid retrieval. - Multimodal agent. . Deep knowledge on ADK , Langchain Agentic Frameworks. . Fine tuning and Distillation . . . 2. Python Expertise. - 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. . 3. GCP Cloud Architecture & Services. - Proficiency in GCP services such as:. - Vertex AI. - BigQuery. - Cloud Storage. - Cloud Run. - Cloud Functions. - Pub/Sub. - Dataproc. - Dataflow. - Understanding of IAM, VPC. 6. API Development & Integration. - Designs and builds RESTful APIs using FastAPI or Flask. - Integrates ML models into APIs for real-time inference. - Implements authentication, logging, and performance optimization. . 7. System Design & Scalability. - Designs end-to-end AI systems with scalability and fault tolerance in mind. - Hands-on experience in developing distributed systems, microservices, and asynchronous processing. Benefits. This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.. .