3 months ago

Staff / Principal Research Engineer, AI Safety, Technical Mitigations

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 15 hours agoStatus: Live

Job Summary

Lead the build-out of safety systems for deploying advanced scientific capabilities, designing and deploying technical safeguards beyond the state of the art. You will guide a small team, define research directions for post-training and classifiers, collaborate with cross-functional safety and non-safety teams, and contribute to external communications on safety efforts.

Location: Cambridge, London, San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Set the build and research strategy for safety systems across data analysis, generation pipelines, safety post-training, refusal classifiers, automated safety-testing, red-teaming systems, and monitoring systems.
•Conduct initial safeguards experimentation and buildout for the organization’s scientific needs, then lead a small team to execute the research agenda.
•Lead safety systems research to iterate beyond the state of the art for in silico and lab-based workflows.
•Partner closely with safety team members (bio/chem/materials) and with core AI, lab automation, and product teams.
•Contribute to external communications on Lila’s safety efforts.

Pay and Benefits

Salary: USD 224,000 - 336,000 annually

Key Requirements

•Track record of building safety systems, classifiers, or conducting post-training for frontier-class problems (science, reasoning, programming, etc.)
•4-6+ years working in technically engineering with ML systems
•Experience building scalable, production systems, not just prototypes
•Demonstrated ability to set research directions for open problems in post-training, classifier buildouts, and other relevant systems
•Ability to communicate complex technical concepts to non-expert audiences effectively

Experience:4-6 yearsAiSafetyMl systems

Skills:CommunicationLeadershipProblem-solving

Languages:English

Tech Stack:MLProduction systemsLab automationPost-training

Company Brief

Lila Sciences

Develops AI-driven platforms to accelerate drug discovery and biological research by integrating machine learning with chemical and biological data to predict molecular properties, streamline candidate selection, and enable faster therapeutic development.

Industry: Biotech

Company Size: Small (11 to 50 employees)

Growth: Early Stage Startup

Funding: Seed

Website LinkedIn

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Lila Sciences

3 months ago

Staff / Principal Research Engineer, AI Safety, Technical Mitigations

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 15 hours agoStatus: Live

Job Summary

Location: Cambridge, London, San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Set the build and research strategy for safety systems across data analysis, generation pipelines, safety post-training, refusal classifiers, automated safety-testing, red-teaming systems, and monitoring systems.
•Conduct initial safeguards experimentation and buildout for the organization’s scientific needs, then lead a small team to execute the research agenda.
•Lead safety systems research to iterate beyond the state of the art for in silico and lab-based workflows.
•Partner closely with safety team members (bio/chem/materials) and with core AI, lab automation, and product teams.
•Contribute to external communications on Lila’s safety efforts.

Pay and Benefits

Salary: USD 224,000 - 336,000 annually

Key Requirements

•Track record of building safety systems, classifiers, or conducting post-training for frontier-class problems (science, reasoning, programming, etc.)
•4-6+ years working in technically engineering with ML systems
•Experience building scalable, production systems, not just prototypes
•Demonstrated ability to set research directions for open problems in post-training, classifier buildouts, and other relevant systems
•Ability to communicate complex technical concepts to non-expert audiences effectively

Experience:4-6 yearsAiSafetyMl systems

Skills:CommunicationLeadershipProblem-solving

Languages:English

Tech Stack:MLProduction systemsLab automationPost-training

Company Brief

Lila Sciences

Industry: Biotech

Company Size: Small (11 to 50 employees)

Growth: Early Stage Startup

Funding: Seed

Website LinkedIn