Applied AI Engineer: Generative Biology in Production

Latent Labs Ltd.; San Francisco (CA); Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Private health insurance

Pension contributions

Generous leave policies

Travel opportunities

Job summary

Latent Labs seeks a Member of Technical Staff to bridge frontier models with customers in pharma/biotech. You will understand proprietary generative models deeply and translate insights into production systems that deliver scientific value, often at customer sites.

You will work across ML researchers, engineers and biologists to deploy, adapt and optimise models, while ensuring performance, reliability and cost-effectiveness in real-world partner environments.

Qualifications

• Strong ML researcher with experience in generative modelling.
• Skilful ML developer writing robust production code and deploying models.
• Customer-facing and delivery-oriented with ability to translate complex concepts.

Responsibilities

• Develop, deploy and adapt Latent Labs models for customer environments.
• Drive end-to-end technical deployment including API integrations and model serving infrastructure.
• Fine-tune models to meet customer requirements with scientific rigor.
• Build ML data pipelines for customer-specific inference and feedback workflows.
• Ensure deployments meet security, performance and reliability standards.
• Collaborate with cross-functional teams and communicate results to customers.

Skills

Generative modelling

ML research

Production code

APIs and model serving

Customer-facing

Model optimization

Tools

Version control systems

Code review tools

Job description

Latent Labs seeks a Member of Technical Staff to bridge frontier models with customers in pharma/biotech. You will understand proprietary generative models deeply and translate insights into production systems that deliver scientific value, often at customer sites.

You will work across ML researchers, engineers and biologists to deploy, adapt and optimise models, while ensuring performance, reliability and cost-effectiveness in real-world partner environments.