Position: Senior Machine Learning Engineer (GCP)

Location: Tlell

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 Big Query, Dataflow, Cloud Functions, Pub/Sub, and GCS in ML workflows.
• Apply CI/CD principles to ML models using Vertex AI Pipelines, Cloud Build, and Git Ops practices.
• Implement model governance, versioning, explainability, and security best practices within Vertex AI.
• Document architecture decisions, workflows, and model lifecycle clearly for internal stakeholders.

Additional expertise required includes:

• Advanced Generative AI, including RAG with Graph-based hybrid retrieval and multimodal agents.
• Deep knowledge of ADK, Langchain Agentic Frameworks, fine-tuning, and distillation techniques.

Python expertise is essential, including:

• Strong OOP and functional programming skills.
• Proficiency with ML/DL libraries such as Tensor Flow, PyTorch, scikit-learn, pandas, Num Py, PySpark.
• Experience with production-grade code, testing, and performance optimization.

GCP Cloud Architecture & Services proficiency includes:

• Vertex AI, Big Query, Cloud Storage, Cloud Run, Cloud Functions, Pub/Sub, Dataproc, Dataflow.
• Understanding of IAM, VPC.

API Development & Integration skills include:

• Designing and building RESTful APIs using FastAPI or Flask.
• Integrating ML models into APIs for real-time inference.
• Implementing authentication, logging, and performance optimization.

System Design & Scalability experience involves:

• Designing end-to-end AI systems with scalability and fault tolerance.
• Developing distributed systems, microservices, and asynchronous processing.

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.

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