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.

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

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.