Develop advanced AI algorithms and neural networks to address specific business and operational challenges within the DB ecosystem

Leverage frameworks like PyTorch and Vertex AI to build models for tasks such as anomaly detection, predictive analytics, NLP, and automating DB processes

Package AI/ML models into scalable APIs and integrate them within production environments and DB systems

Monitor and refine AI/ML models to improve precision, scalability, and efficiency using diverse datasets

Collaborate with DB engineers, data scientists, product managers, and business stakeholders to align AI initiatives with organizational goals

Ensure data quality through industry-standard practices for data cleaning, transformation, and validation

Research technological advancements in AI/ML and explore new tools and frameworks to introduce innovative solutions in the DB team

Troubleshoot system and model-related issues and enhance inference speed and system productivity

Validate data integrity and ensure dependable and accurate outputs from AI solutions

Model decision-making processes or automate complex workflows that seamlessly interact with data infrastructure

3+ years of experience in AI/ML, data engineering, or closely related fields

Proficiency in Google Gemini, Vertex AI, and PyTorch demonstrated through practical projects

Competency in BigQuery, Apache Airflow, and ELK Stack for tasks like orchestration, analytics, and monitoring

Background in developing and deploying AI models, APIs, and machine learning pipelines in production

Expertise in large-scale data management, including processing, cleaning, and transformation

Capability to diagnose AI systems, perform diagnostics, and enhance performance

Understanding of generative AI models and their real-world applications to business scenarios

Showcase of effective communication skills in English, both spoken and written, at B2 level or higher