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Tiger Analytics Inc.

Machine Learning Engineer (with Vertex AI Experience)

LocationCanada
Typefull-time
DepartmentMLE
Company size5,001–10,000 people
First seenOct 5, 2026 · 6d ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Must have13
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
Skills
Google Cloud Platform
Vertex AI
BigQuery
Dataflow
Cloud Functions
Pub/Sub
Cloud Storage
Cloud Run
Dataproc
Python
TensorFlow
PyTorch
scikit-learn
pandas
NumPy
PySpark
FastAPI
Flask
Langchain
ADK
About the role
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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