Bio-AI & ML Ops Science Lead

Procter & Gamble; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Procter & Gamble Singapore at Biopolis seeks a leader to design, develop, evaluate, and scale predictive Bio-AI and integrated Consumer data models and multi-agent workflows. You will transform trusted data, knowledge, and domain tools into governed AI solutions that predict outcomes and guide experimentation.

You will drive ML Ops/LLM Ops, CI/CD, evaluation frameworks, and scalable platform capabilities, collaborating with scientists, bioinformaticians, and data engineers across the region.

Qualifications

• Bachelor's/Master's/PhD in Data Science, Bioinformatics, Computational Biology, Biostatistics or related field.
• Strong Python engineering and hands-on experience delivering AI/ML/data solutions.
• Experience developing and deploying predictive models, LLM apps, retrieval systems or agentic workflows.
• Experience with tool calling, structured outputs, workflow orchestration, and agent state or memory.
• Experience designing evaluation approaches for ML/LLM/agentic AI systems.
• Familiarity with APIs, cloud deployment, containers, CI/CD, monitoring, and ML Ops/LLM Ops.

Responsibilities

• Build predictive and agentic AI solutions with multi-agent scientific workflows for evidence retrieval, hypothesis generation, and decision support.
• Deploy, validate, and scale AI capabilities with evaluation, CI/CD, observability, and governance.

Skills

Python

ML/AI implementation

Data modeling

Retrieval systems

Agentic workflows

Experiment planning

Education

Bachelor's/Master's/PhD in Data Science or related

Tools

APIs

Cloud deployment

Containers

CI/CD

Monitoring

Job description

Procter & Gamble Singapore at Biopolis seeks a leader to design, develop, evaluate, and scale predictive Bio-AI and integrated Consumer data models and multi-agent workflows. You will transform trusted data, knowledge, and domain tools into governed AI solutions that predict outcomes and guide experimentation.

You will drive ML Ops/LLM Ops, CI/CD, evaluation frameworks, and scalable platform capabilities, collaborating with scientists, bioinformaticians, and data engineers across the region.