Generative AI Research Engineer: Build & Deploy

Google DeepMind; Singapore; On-site; SGD 110,000 - 170,000; Full time

Benefits offered by this job

Learning opportunities

Global teams

Job summary

Google DeepMind in Singapore seeks a Research Engineer to lead development and deployment of novel applications using Google GenAI models. You will rapidly build features, collaborate with partner teams, and translate cutting‑edge AI research into real‑world products that scale for premier customers.

The role requires a strong software engineering foundation, experience shipping production code, and a track record in early‑stage or startup environments where ownership and rapid iteration drive

Qualifications

• Bachelor's degree or equivalent practical experience in CS/EE or related field.
• 8 years of software development with one or more languages (e.g., Python).
• 5 years of ML design and deployment experience, incl. evaluation and fine‑tuning, plus RL experience.
• 3 years in software architecture and launching products.

Responsibilities

• Collaborate with cross-functional teams to define product objectives and designs.
• Curate datasets and design evaluations across various industry verticals.
• Lead development of novel solutions from 0 to 1 using internal platforms and foundation models.
• Share real‑world evaluations and deployment signals with core research teams.
• Act as technical lead for genAI deployment and end‑to‑end problem solving.

Skills

Software development

ML design

Model deployment

Python

Reinforcement learning

Testing & launching

Education

Bachelor's degree in Computer Science or related field

Tools

TensorFlow

PyTorch

Hugging Face

Google Cloud Platform

Job description

Google DeepMind in Singapore seeks a Research Engineer to lead development and deployment of novel applications using Google GenAI models. You will rapidly build features, collaborate with partner teams, and translate cutting‑edge AI research into real‑world products that scale for premier customers.

The role requires a strong software engineering foundation, experience shipping production code, and a track record in early‑stage or startup environments where ownership and rapid iteration drive