At a Glance
- Tasks: Design and deploy scalable ML solutions using Google Cloud Platform and Vertex AI.
- Company: Join a fast-growing tech company focused on innovative machine learning solutions.
- Benefits: Great career growth, individual responsibility, and a dynamic entrepreneurial environment.
- Other info: Collaborate with talented teams and drive the end-to-end ML lifecycle.
- Why this job: Make an impact in the AI field while working with cutting-edge technologies.
- Qualifications: Expertise in Python, GCP services, and machine learning frameworks required.
The predicted salary is between 58500 - 71500 $ per year.
- Vertex AI
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, Auto ML, 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 Big Query, Dataflow, Cloud Functions, Pub/Sub, and GCS in ML workflows.
- Apply CI/CD principles to ML models using Vertex AI Pipelines, Cloud Build, and Git Ops 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
- Python Expertise
- Expert in Python with strong OOP and functional programming skills
- Proficient in ML/DL libraries: Tensor Flow, Py Torch, scikit-learn, pandas, Num Py, Py Spark
- Experience with production-grade code, testing, and performance optimization
- GCP Cloud Architecture & Services
• Proficiency in GCP services such as
- Vertex AI
- Big Query
- Cloud Storage
- Cloud Run
- Cloud Functions
- Pub/Sub
- Dataproc
- Dataflow
- Understanding of IAM, VPC
- API Development & Integration
- Designs and builds RESTful APIs using Fast API or Flask
- Integrates ML models into APIs for real-time inference
- Implements authentication, logging, and performance optimization
- 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.
Senior Machine Learning Engineer (GCP) in Ottawa employer: Tiger Analytics
Tiger Analytics is an exceptional employer that fosters a collaborative and innovative work culture in the heart of Toronto. With a strong focus on employee growth, we offer ample opportunities for professional development and skill enhancement, particularly in cutting-edge technologies like Neo4j. Our commitment to work-life balance and a supportive environment makes us an ideal place for those seeking meaningful and rewarding careers in data governance and architecture.
