Machine Learning Engineer (with Vertex AI Experience)

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

4. 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

5. 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.