Senior Machine Learning Engineer (GCP)

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.