Machine Learning Engineer (with Vertex AI Experience)
Tiger Analytics Inc. Open · verified Oct 24, 2026 At a glance
Mid-level Machine Learning Engineering role at Tiger Analytics Inc. Remote, Canada · no salary stated · we estimate CA$127,500–CA$185,000 across Canada.
Tiger Analytics Inc. has not published a salary for this role. The figure below is our estimate, not theirs.
remoteroles summary, based on the employer's posting.
What you'll do
- Build and tune models in Vertex AI, using Vertex Pipelines, AutoML or custom training approaches
- Create ML pipelines that handle feature preparation, model training, evaluation and release
- Serve models through Vertex AI endpoints and connect them to applications or APIs
- Track model behavior with drift checks, alerts and retraining triggers, while applying governance and version controls
- Use GCP services and CI/CD practices to support repeatable ML workflows and document their architecture
What you bring
- You have advanced generative AI skills, including hybrid retrieval, multimodal agents and model fine-tuning
- You bring expert Python ability and experience with ML libraries, production code, testing and performance tuning
- You can work with Vertex AI and other GCP services, including cloud architecture concepts such as IAM and VPC
- You have built REST APIs for real-time model inference and understand authentication, logging and performance needs
- You can design scalable AI systems and have hands-on experience with distributed systems or microservices
Who this fits
This mid-level, remote role is based in Canada. It suits an engineer who can take ML work from model development through deployment, monitoring and integration.
From the employer
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
Benefits
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.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
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