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).
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.
AI Frontier · AI scientific discovery
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 |
|---|---|---|
| Senior ML Scientist, Biological Systems Seeking a Senior ML Scientist to build autonomous life science systems that connect AI reasoning, biological evidence, experimental design, and automated execution. The role involves translating scientific direction into working architectures, workflows, and evaluation methods, with a focus on rigorous reasoning about biological hypotheses, proposing experiments, and incorporating evidence to accelerate discovery. This is a hands-on role at the intersection of ML, biological reasoning, agentic systems, and experimental design. | AgentEval Gate | 9 |
| Principal Scientist / Associate Director, Agentic AI Research for Materials Science Principal Scientist / Associate Director, Agentic AI Research for Materials Science. Owns technical direction for agentic AI systems applied to materials science, setting and executing roadmaps for autonomous agents that plan, run, and interpret materials experiments. This player-coach role leads a small team, bridges foundational research and applied delivery, and ships systems for materials teams. Requires PhD, 5+ years post-PhD experience, track record of building/shipping agentic systems, deep expertise in LLMs, agentic frameworks, tool use, planning, data extraction, multi-modal data, and familiarity with materials science. Python and ML software stack proficiency with strong engineering habits are essential. Experience leading scientists/engineers is required. | AgentData | 9 |
| Senior / Principal Scientist, AI for Protein Engineering Senior/Principal Scientist role focused on AI for protein engineering, specifically antibody design and engineering. The role involves developing and executing design workflows, translating biological requirements into ML problems, adapting state-of-the-art AI methods, and collaborating with experimental scientists for validation and active learning loops. The position requires a PhD and strong expertise in both ML and protein biology, with a focus on delivering wet-lab validated biomolecules. | DataPost-train | 9 |
| ML Scientist I / II, Foundation Models for Life Sciences Research Scientist role focused on developing and evaluating foundation models for life sciences applications, including biological sequence design, structure prediction, and multimodal scientific reasoning. The role involves end-to-end ML process contribution, from data generation strategy to feedback loops, and collaboration with experimental scientists. Requires a strong foundation in generative models and ML frameworks, with a PhD or equivalent research experience. | PretrainPost-train | 9 |
| Principal, Machine Learning Engineer Principal ML Engineer at Lila Sciences, focusing on building and scaling ML infrastructure for generative models in medicine. The role involves owning end-to-end systems from training pipelines and distributed compute to model deployment and integration into a closed-loop discovery engine. Key responsibilities include designing and optimizing large-scale training pipelines, owning production ML systems, architecting ML infrastructure, driving the "Lab-in-the-Loop" lifecycle, and defining ML engineering standards. The role requires deep expertise in distributed training, production ML systems, and strong software engineering fundamentals, with a focus on generative models for biological data. | DataServe | 9 |
| Senior / Principal ML Scientist, Foundation Models for Life Sciences Research Scientist role focused on developing and training large-scale generative foundation models for life sciences applications, including biological sequence design and molecular structure prediction. The role involves end-to-end ML process from problem formulation to integration into a closed-loop discovery engine, with a strong emphasis on research and publications. | PretrainPost-train | 9 |
| Staff / Principal Research Engineer, AI Safety, Technical Mitigations This role focuses on building and implementing AI safety strategies and systems for the safe deployment of scientific capabilities, involving technical safety strategy development, safety-focused evaluations, and a safety research agenda. It requires experience in building safety systems, classifiers, or post-training for frontier-class problems and scalable production systems. | Post-trainEval Gate | 9 |
| Machine Learning Scientist I/II, Multi-Modal Scientific Reasonings Research role focused on advancing multi-modal reasoning with vision-language models (VLMs) on scientific data, including figures, plots, and microscopy. The role involves designing and building state-of-the-art methods for scientific understanding tasks, developing perception modules, and creating datasets and benchmarks. Collaboration with domain scientists and engineers to scale research into production systems is key. | Post-trainAgent | 9 |
| ML Research Scientist I/II, Multimodal Data Extraction Research Scientist role focused on developing foundation models for multimodal data extraction in scientific domains, involving fine-tuning LLMs and vision-language models, and building data pipelines. | Post-trainAgent | 9 |
| Research Scientist, Frontier Capabilities Research Scientist role focused on developing next-generation learning systems and reasoning algorithms for agentic LLMs, particularly in scientific domains with sparse and delayed feedback. The role involves building agentic systems that autonomously propose, execute, and verify scientific hypotheses, or focusing on distillation techniques to create efficient models, or developing scalable experience generation and synthetic data pipelines for training. Requires advanced degree, strong LLM foundation, and ML experiment experience. | Post-trainAgent | 9 |
| Research Engineer, Frontier Capabilities Research Engineer focused on training LLMs for long-horizon scientific discovery tasks, spanning the post-training stack from SFT to asynchronous RL on agentic harnesses. The role involves designing, building, and optimizing systems for scaling post-training, sharpening reasoning, and enabling compute-intensive agentic-harness training. Specific work streams include GPU optimization, stack and infrastructure development, model experimentation, evaluations and benchmarks, and agentic capabilities research. | Post-trainAgent | 9 |
| Senior / Engineer II, AI Lab Research Engineer This role focuses on building agentic AI systems for scientific discovery, including workflow/code generation and evaluation mechanisms. It requires expertise in LLMs, agent architectures, and ML frameworks, with a strong emphasis on adapting these to scientific domains. Experience with long-horizon agents, RL, and evaluation design is highly valued. | AgentEval Gate | 9 |
| Research Product Manager, Post Training Research Product Manager to set the vision for Lila’s foundational models, defining capabilities and performance that turn breakthrough research into real-world scientific impact. Owns the capability roadmap for core foundational model releases, synthesizing input from various stakeholders into a prioritized roadmap. Defines evaluation criteria, success metrics, and gating criteria for promoting models to production. Partners with research and model-training leads, and maintains documentation. | Post-trainEval Gate | 8 |
| Senior / Staff Machine Learning Engineer, Applied AI Senior/Staff Machine Learning Engineer at Lila Sciences focused on improving AI models for customer-specific scientific needs by training, evaluating, and deploying LLMs and multi-modal models. The role bridges research and engineering, translating frontier capabilities into reliable, production-quality systems and workflows. | Post-trainAgent | 8 |
| Co-Op, LS AI, ML Scientist for Protein Engineering ML Scientist Co-Op role focused on protein engineering research, including generative protein design and antibody engineering. The role involves exploring generative and predictive modeling approaches for biomolecules, analyzing biological datasets, and prototyping workflows that connect model predictions with wet-lab feedback. This is an applied ML research position at the intersection of AI and biology. | Post-train | 8 |
| Co-Op, ML Scientist for Biology Research role focused on developing autonomous-science capabilities in life sciences using AI and automation. The role involves exploring reasoning models, evaluating and reinforcing agentic model behavior, developing benchmark datasets, analyzing multi-modal biological data, and prototyping workflows connecting AI reasoning with scientific feedback. | AgentEval Gate | 8 |
| Head of Software Product Head of Software Product to lead the strategy and development of an "Agentic Superscience" software platform that reinvents the scientific method using AI agents for materials, chemistry, and biology experiments. The role involves building the platform, creating cross-functional integration, delivering user interfaces, and owning the product lifecycle. | Agent | 8 |
| 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 |
| AI Residency Program, Material Science (2026 Cohort) Research residency program focused on applying AI/ML to materials science, exploring areas like ML-accelerated simulations, generative models, and agentic science. The role involves designing and executing independent research projects, collaborating with scientists, and contributing to open-science initiatives. While publishing is encouraged, the core focus is on advancing scientific discovery. | Pretrain | 8 |
| Senior Director, Software Development, Test Automation Senior Director of Software Development, Test Automation Systems to architect and build Lila's test automation platform and quality engineering practice for AI-powered scientific and lab automation products. This role owns the test automation system, CI/CD test infrastructure, AI-driven test tooling, and the eval discipline. Responsibilities include designing and building the test automation platform, making build-vs-buy decisions, modernizing CI/CD, driving AI-driven test automation, defining quality metrics, and standing up the QC framework for lab automation. The role also involves leading and coaching across the engineering org and building a team. | AgentEval Gate | 7 |
| Co-Op, Autonomous SEM Seeking a Co-Op, Autonomous SEM to join the Materials Science team, focusing on developing autonomous SEM workflows for characterization. This role involves building practical autonomy for scientific instruments, including navigation logic, image quality evaluation, and connecting imaging decisions to downstream analysis and ML training. | AgentData | 7 |
| Co-Op, Automation The role involves building data pipelines for real-time anomaly detection, training detection models to identify deviations from expected operating envelopes, and developing alerting workflows for operators. This is for a scientific superintelligence platform in life, chemistry, and materials science. | AgentData | 7 |
| Director/Senior Director, Molecular Discovery Director/Senior Director, Molecular Discovery at Lila Sciences responsible for the output, quality, and operational health of an autonomous science platform that generates and tests hypotheses for small-molecule drug candidates. This role requires deep fluency in medicinal chemistry principles and AI/ML-driven molecular design, acting as a key interface between computational predictions and experimental results to advance compounds toward the clinic. | Ship | 7 |
| Co-op, Machine Learning for Digital Twins The role involves building, training, and evaluating ML models for physical and experimental systems, focusing on digital twins, operator learning, surrogate modeling, and uncertainty quantification. The work directly influences the design and operation of AI Science Facilities. | Post-train | 7 |
| Co-Op, Data Extraction The role involves contributing to AI systems for knowledge extraction from scientific literature and patents. Responsibilities include fine-tuning and evaluating language/multimodal models, building data structuring pipelines, running extraction pipelines, analyzing results, and documenting findings. The goal is to ship work that integrates into production systems. | Post-trainServe | 7 |
| Co-Op, AI Security Co-Op role focused on AI security within the IT & Security team, evaluating, hardening, and monitoring AI tools, agents, and automation pipelines. Responsibilities include identifying vulnerabilities (prompt injection, model poisoning), threat modeling, reviewing code, researching threats, and developing security tests for AI models and agents. | Agent | 7 |
| Senior Software Engineer, App The role focuses on designing and building the AI-native platform, including agents, interfaces, and platform integrations, that enables researchers to seamlessly collaborate with AI. This involves developing UI and APIs, managing diverse data systems (including Vector DBs), driving full-stack application development, optimizing performance and reliability, and leveraging cloud infrastructure. The team works at the intersection of AI and science, connecting AI to lab workflows and ML pipelines. | AgentServe | 7 |
| Sr Principal/Principal Software Engineer, App Sr Principal/Principal Software Engineer to design agents, interfaces, and platform integrations for researchers to collaborate with AI. The role involves building UI/APIs, database architecture, application development, performance optimization, and cloud infrastructure, with a focus on integrating AI into scientific workflows. | AgentServe | 7 |
| Contractor, Robotics Engineer Robotics Engineer contractor to integrate, tune, and debug physical hardware and simulation systems for inter- and intra-cell transport in an AI-driven scientific facility. The role involves ROS2 development, motion planning, and hardware integration, with deliverables gating upstream science projects. | Ship | 7 |
| 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. | Serve | 7 |
| Vice President, Engineering VP of Engineering to build and scale a unified platform for autonomous experimentation in AI Science Factories, integrating AI into lab science, automation, hardware, and systems engineering. Focus on strategy, execution, and talent for global expansion. | Ship | 7 |
| Principal Engineer, AI Security Principal Engineer, AI Security role focused on defining and driving the technical strategy for securing AI usage across Lila's enterprise. This role partners with IT and business teams to ensure safe and compliant adoption of AI tools and platforms, focusing on protecting sensitive data, intellectual property, and scientific workflows. Responsibilities include defining security controls and guardrails for AI tools, designing AI gateway and agentic gateway security, conducting red teaming and adversarial testing, developing data protection controls, integrating AI security into enterprise security layers, threat modeling, vendor assessment, and incident response. | Agent | 7 |
| Product Lead, Software/Applied AI Product Lead for an AI-native system of record for scientific discovery, focusing on building tools that accelerate scientific research. The role involves deep domain ownership, full-stack product execution, and cross-functional orchestration between research and engineering teams. Priority areas include data, ML/computational tooling, scientific agents, and harness & evals. Requires strong product management experience in complex B2B SaaS or technical platforms, comfort with ambiguity, and a bias for action. Scientific background and experience building for scientists are preferred. | AgentData | 7 |
| Director, Data Platform Engineering Director of Data Platform Engineering to lead a team responsible for Lila's product data platform, owning the end-to-end architecture, delivery, reliability, and developer/data scientist experience. The platform supports analytical and ML workloads, including AI inference workflows. The role involves team leadership, technical strategy, stakeholder management, and driving innovative solutions for data interfaces, exploration, query, analytics, and ML/inference at scale. | DataServe | 7 |
| Director of Product, Life Sciences Director of Product, Life Sciences at Lila Sciences, responsible for shaping the future of therapeutic R&D by leading the strategy, roadmap, and execution for products and platforms at the intersection of drug discovery, chemical synthesis, and scientific intelligence. This role drives AI capabilities towards breakthrough solutions, translates strategic objectives into development campaigns, and leads cross-functional teams. | Data | 7 |
| Senior Software Engineer, ML Research Senior Software Engineer to build and maintain ML libraries, tools, and research infrastructure, focusing on performance, security, and MLOps. The role involves designing libraries, CI/CD pipelines, and supporting compute environments, with a strong emphasis on software engineering best practices within an ML research context. | Data | 7 |
| Senior Software Engineer, Applied AI Senior Software Engineer to join Applied AI group to build the next generation of their AI-driven scientific platform. Role involves designing and optimizing backend systems, data pipelines, and AI integrations for intelligent, data-driven applications, working at the intersection of backend engineering and machine learning. Focus on scaling and supporting applied AI techniques like RAG, agentic AI, and LLM integration, turning research into production-grade systems. | AgentServe | 7 |
| Staff Forward Deployed Engineer, Physical Sciences (Level Flexible) The Forward Deployed Engineer (FDE) role at Lila Sciences focuses on embedding with internal biotech and materials science teams, as well as external customers, to build and deploy AI-fueled solutions. This involves developing domain-specific tools, deploying agentic scientific workflows integrated with industrial instruments and data systems, building real-time data pipelines, creating user interfaces for AI/ML capabilities, and architecting scalable solutions. The role requires strong full-stack development skills, data engineering experience, and domain expertise in chemistry or materials science, with a focus on rapid, production-level code delivery. | AgentServe | 7 |
| Staff Forward Deployed Engineer, Life Sciences Seeking Forward Deployed Engineers to embed with internal biotech and external customers, building AI-fueled solutions to transform research capabilities. This role involves developing domain-specific tools, deploying agentic scientific workflows, building real-time data pipelines, creating user interfaces for AI/ML, and architecting scalable solutions. | AgentServe | 7 |