Lila Sciences
AI Frontier · AI scientific discovery
Currently tracking 39 active AI roles, down 40% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $128k–$500k (avg $253k).
AI Frontier · AI scientific discovery
Lila Sciences currently has 53 active AI-related job listings. The majority of these roles are in the agents stage, accounting for 43% of the openings. Engineering is the top function for hiring, followed by Research. The company is primarily hiring in the United States. Frequently tagged technologies include agent orchestration, model serving, and evals, suggesting a focus on agent-based AI systems and their deployment. Over the last 30 days, Lila Sciences has posted 12 new AI roles, representing a 25% decrease compared to the previous 30-day period.
Lila Sciences currently has 51 active AI-related roles in our index. The most common open titles are: AI Residency Program, Material Science (2026 Cohort), Co-Op, AI Security, Co-Op, Automation, Co-Op, Autonomous SEM, Co-Op, Data Extraction. Most positions are in Engineering and Research.
Lila Sciences's active AI hiring is concentrated in: agents (43%), data (22%), post-training (20%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Lila Sciences is hiring AI talent in: United States (51 roles).
Job postings at Lila Sciences most frequently mention: Materials Science, Biotech, Machine Learning, Python, Software Engineering.
In the past 30 days, Lila Sciences has posted 10 new AI-related roles. That is a -37% change versus the prior 30 days (16 → 10).
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Engineer II / Senior Machine Learning Engineer I, Physical Sciences Machine Learning Engineer role focused on building and operating end-to-end, scalable ML workflows for scientific use cases in materials, chemistry, and physical sciences. The role involves designing, implementing, and maintaining ML pipelines, productionizing models and services, and collaborating with domain scientists and platform engineers to translate research insights into scalable systems. Experience with model deployment in production, including LLMs and multimodal models, is required. | ServeAgent | 8 |
| Staff ML Engineer, Life Sciences AI Staff ML Engineer role focused on building and operating the software infrastructure for AI-driven protein design and engineering pipelines, connecting generative models, scientific data, and experimental workflows. This role emphasizes scalable production systems, pipeline orchestration, data flow, and integrating new ML tools into commercial deliverables. |
| 7 |