Your Impact at LILA

Lila Sciences is seeking Platform Scientists, Soft Materials Focus to ideate, prototype, and transfer new experimental concepts for AI Science Factories targeting complex and soft material systems. In this role, you will work at the forefront of scientific ideation—partnering with a broad range of chemistry, materials, and AI teams to define new approaches to formulation, structure–property relationships, and performance evaluation. You will translate these concepts into scalable experimental workflows, custom apparatus, and software-enabled systems for autonomous research.

What You'll Be Building

• Collaborate with diverse scientific teams to ideate new experimental strategies for soft and complex materials, including formulations, colloids, polymers, gels, and biological or hybrid systems
• Lead conceptual development of characterization and performance workflows leveraging techniques such as SAXS, SANS, rheology, and formulation performance assays
• Design, prototype, and validate custom apparatus, experimental methods, and software tools to realize these concepts
• Develop and refine workflows that connect structure, dynamics, and performance across multiple length and time scales
• Transfer successful prototypes into production-ready systems within Lila’s AI Science Factory platform, enabling autonomous experimentation

What You’ll Need to Succeed

• MS or PhD in Materials Science, Chemistry, Chemical Engineering, Physics, or a related field, with a focus on soft or complex materials
• Demonstrated experience collaborating across scientific disciplines to generate and refine experimental concepts
• Hands-on experience with one or more of the following: SAXS, SANS, rheology, formulation performance or functional assays
• Experience designing and implementing custom experimental workflows and/or scientific software
• Strong programming skills (e.g., Python, C++, or similar) applied to data analysis, automation, or experiment control
• Excellent communication skills and comfort operating in a fast-paced, exploratory R&D environment

Bonus Points For

• Experience with lab automation, high-throughput experimentation, or instrument control software
• Background in formulation science (e.g., consumer products, coatings, energy materials, bio-soft matter)
• Experience linking scattering, rheological, and performance data to predictive or ML-driven models
• Familiarity with prototyping tools such as 3D printing, machining, microfluidics, or custom sample environments
• Industry or national lab experience working on soft materials or complex fluids

Your Impact at LILA

As a Machine Learning Scientist focused on Scientific Reasoning, you will help pioneer the next generation of AI systems capable of reasoning like a scientist. You’ll design novel frameworks that push the boundaries of LLM-based reasoning methods — while also implementing scalable frameworks that integrate with Lila’s platforms. This role bridges deep theoretical thinking with practical ML engineering, enabling breakthroughs in how scientific hypotheses are generated, tested, deployed and optimized.

What You'll Be Building

• Design and formalize frameworks for scientific reasoning with LLMs, including structured prompting, reasoning chains, and test-time compute.
• Explore and implement methods for in-context learning, self-reflection, and adaptive reasoning in scientific discovery workflows.
• Build scalable model prototypes that can be deployed to solve frontier scientific problems.
• Collaborate with scientists and engineers to encode domain knowledge into reasoning systems that integrate symbolic and statistical approaches.

What You’ll Need to Succeed

• PhD (preferred) or equivalent research/industry experience in Computer Science, Machine Learning, AI, Engineering, Materials Science or related fields.
• Strong programming skills in Python with deep expertise in LLM frameworks (PyTorch, HuggingFace Transformers, LangChain, LlamaIndex, and related toolkits).
• Expertise in LLM reasoning methods: in-context learning, test-time compute, chain-of-thought, or tool-augmented reasoning.
• Ability to balance theoretical research with practical ML engineering to deliver scalable solutions.

Bonus Points For

• Research experience in causal reasoning, symbolic AI, or probabilistic programming.
• Contributions to open-source LLM reasoning frameworks.
• Familiarity with scientific discovery pipelines in chemistry, biology, or materials science.
• Experience with multimodal reasoning (e.g., combining text, image, and experimental data).
• Publications in top ML/AI conferences (NeurIPS, ICML, ICLR, ACL).

Your Impact at LILA

Lila Sciences is seeking a detail-oriented and process-driven HR Generalist (Contract) to join our HR Operations team. This role will serve as the execution backbone of our HR Operations function. The HR Generalist will handle the day-to-day administration of the employee lifecycle, systems management, benefits support, and cross-functional HR tasks. This is a high-execution role best suited for someone who takes pride in doing administrative work accurately and efficiently, thrives on process ownership, and is energized by bringing order and consistency to a growing organization.

What You'll Be Building

Employee Lifecycle, Onboarding & Offboarding

• Execute end-to-end pre-boarding and onboarding processes, including coordination of IT intake, systems access setup, and employee introduction materials
• Identify and implement improvements to pre-boarding workflows to increase consistency and reduce manual effort
• Support offboarding administration, including exit paperwork and required system updates
• Process administrative HR actions across the employee lifecycle: new hires, transfers, internal role changes, manager changes, and terminations
• Generate employment letters (transfer, termination, etc.) and manage signature request workflows
• Maintain and organize employee documentation in accordance with compliance requirements

Immigration & Benefits Administration

• Manage immigration paperwork and coordinate with external counsel or vendors on active cases under HR Operations Manager guidance
• Administer benefits tasks that cannot be automated, including enrollment support and data entry
• Provide leave administration support as needed, in coordination with HRBPs

HR Inbox & Employee Support

• Manage the HR team inbox: triage, respond to, and route inquiries related to onboarding/offboarding, immigration, benefits, and company policies
• Serve as a reliable first point of contact for employee and manager HR questions, ensuring timely and accurate responses, and escalating complex cases appropriately

Process & Compliance

• Own the I-9 compliance process end-to-end: complete Section 2 verification for all new hires, manage re-verification for expiring work authorization documents, maintain organized and audit-ready I-9 records, and coordinate E-Verify submissions where applicable
• Collaborate with HR Operations to document, standardize, and improve HR workflows and procedures

What You’ll Need to Succeed

• 1–3+ years of HR experience with a focus on HR operations, administration, or HR coordination
• Hands-on experience with HRIS platforms; HiBob and/or ADP experience is a plus
• Strong attention to detail and a track record of accurate, high-volume administrative work
• Comfortable managing multiple competing priorities with minimal supervision
• Clear and professional communicator (written and verbal)
• Ability to handle sensitive, confidential HR information with discretion
• Demonstrated commitment to process improvement and operational consistency
• Local to the Cambridge, MA area; able to work hybrid (averaging ~3 days/week onsite based on need)

Bonus Points For

• Experience with ATS platforms (e.g., Greenhouse)
• Direct experience administering the I-9 process
• Experience with process documentation and process flow documents
• Familiarity with immigration processes and vendor coordination
• Experience supporting benefits administration or leave management
• Comfort with ambiguity in a fast-paced, evolving environment

Overview of the role:

As the Product Manager for Software / Applied AI at Lila, you will help build the first truly AI-native system of record for scientific discovery. We are looking for product leaders who can dive deep into a specific domain and own it completely.

Whether your strengths align best with our core software platform or our cutting-edge agentic science offerings, you will be embedded with a dedicated scrum team to solve complex, full-stack challenges. You will sit at the intersection of commercial, engineering, design, and scientific research, building the tools that accelerate the next generation of scientific discovery.

We are hiring for a wide range of function areas, and seniority levels — final title and level will be decided at the offer stage. Priority areas include 1) data, 2) ML / computational tooling, 3) scientific agents, and 4) harness & evals.

Location:

Ability to work from our San Francisco, CA; or Cambridge, MA office 3-5 days per week.

Responsibilities:

Deep Domain Ownership:

We will match your unique product strengths to a specific scrum team, where you will go deep, define the roadmap, and become the absolute subject matter expert for that product area. That said, we operate as one product team and collaborate closely.

Full-Stack Product Execution:

From designing user-facing scientific workflow tools to shaping the underlying data infrastructure that powers our AI models, you will define requirements and guide execution across the entire stack.

The intelligence platform for Science:

Build intuitive, powerful software that scientists actually want to use. You will be responsible for translating incredibly complex scientific workflows into scalable, elegant digital products.

Cross-Functional Orchestration:

Lead the dialogue between our research scientists (who push the boundaries of what's possible) and our engineering teams (who build robust, scalable systems), ensuring we ship high-impact, cohesive products.

Qualifications:

Core Product Experience:

Product Management experience building complex B2B SaaS, data-heavy platforms, or highly technical software products.

The Full-Stack Mindset:

You are comfortable navigating both the user experience of a complex workflow and the technical realities of the backend architecture required to support it.

Bias for Action in Complexity:

You thrive in ambiguous environments. You can take a vague, highly technical customer request and turn it into a clear, prioritized roadmap for your engineering team in days, not weeks.

Operational Rigor:

You care deeply about the "how" — how the product is built, how it performs, and how it directly impacts the end user's daily work.

Preferred Skills:

Scientific Background:

A degree or deep practical experience in the hard sciences (materials science, chemistry, biology, etc.).

Building for Scientists:

Direct experience building software, tools, or platforms specifically designed for scientific researchers or lab environments.

Startup DNA:

Experience as an early-stage product manager who knows how to move fast, iterate, and build from 0 to 1.

Your impact at LILA

We’re building a talent-dense, high-agency research team to develop the next generation of learning systems and reasoning algorithms for agentic LLMs. Our work sits at the intersection of large language models, post-training, and scientific reasoning, with the goal of enabling systems that learn from experience, reason effectively, and improve through interaction.

Scientific domains present a distinct set of challenges that make this problem uniquely hard. Feedback is sparse and delayed — experiments take days or weeks, not milliseconds. Ground truth is expensive or contested. Distribution shift is structural, as instruments, techniques, and knowledge bases evolve continuously. The hypothesis space is vast and reward signal is thin. Existing benchmark do not capture these nuances. The goal is to build systems that can operate effectively in this scientific regime.

This role spans a few complementary directions. Candidates are expected to bring deep expertise in one (ore more) of the following areas. In the event of cross-track expertise, please select the one you align to the most. Our interview process will be catered to verifying the chosen expertise area.

Expertise Area 1 — Agentic system building

Focus: Build systems that autonomously propose, execute, and verify scientific hypotheses over long time horizons.

• Create and analyze long-running auto-research systems that propose and verify hypotheses
• Design planning frameworks for agentic systems operating over long, sparse feedback loops
• Design memory architectures that allow agents to build and retrieve structured knowledge over time
• Explore algorithms in recursive self-improvement, multi-agent coordination, and continual learning

Expertise Area 2: Distillation

Focus: Translate strong inference-time behaviors and reasoning traces into efficient, trainable models.

• Develop distillation strategies from large or ensemble models into deployable systems
• Research methods for self-improvement, including iterative self-distillation and critique loops
• Investigate how to preserve generalization and reduce catastrophic forgetting through the distillation process

Expertise Area 3 — Scalable experience generation

Focus: Develop inference-time algorithms and synthetic data pipelines that generate high-quality training signal for scientific reasoning.

• Design and benchmark inference-time search, sampling, and verification strategies
• Propose new techniques in synthetic environment creation and curriculum learning
• Develop synthetic data generation strategies that capture high-quality scientific reasoning for agentic model training
• Measure the end-to-end impact of inference-time improvements on real scientific tasks

What you’ll need to succeed:

• An advanced degree in computer science, machine learning, or a related field, or or comparable experience
• Strong foundation in LLMs and empirical research
• Experience designing and executing rigorous ML experiments, including benchmarking and ablations
• Experience working with large-scale training or evaluation pipelines
• Ability to define and pursue research directions in open-ended, rapidly evolving spaces
• Strong collaboration and communication skills across research and engineering teams

Bonus points for:

• Experience with synthetic data generation, distillation, or self-improvement loops
• Familiarity with reinforcement learning (e.g., RLHF, on-policy methods)
• Experience with planning, search, or decision-making systems at scale
• Experience in building agentic systems with tool use, or multi-agent workflows
• Background in program synthesis, coding benchmarks, or long-horizon tasks
• Experience building evaluation frameworks or large-scale benchmarks

Scientific rigor & persistence:

• You take a principled approach to experimentation, with careful baselines, ablations, and evaluation design
• You are motivated by understanding why systems work, not just improving metrics
• You prioritize clarity, reproducibility, and intellectual honesty in research
• You are comfortable working through long, nonlinear iteration cycles
• You operate effectively in ambiguous, fast-evolving research environments

Your Impact at LILA

The AI Research team is tackling one of the most exciting, open problems in AI: training LLMs to run long-horizon scientific discovery tasks. Our approach spans the full post-training stack - from SFT to asynchronous RL on agentic harnesses - teaching models to plan, use tools, and learn from experience in domains where the ground truth isn't a preference label, but a scientific result.

We're rapidly growing our Research Engineering org and seeking talented engineers and ML practitioners across levels to design, build, and optimize systems to push this frontier: scaling post-training, sharpening reasoning, and unlocking compute-intensive agentic-harness training. This is a rare chance to join an early team with the autonomy, flexibility, and compute to tackle frontier science problems.

We operate with high agency, and a bias toward execution. Below are several focus areas within the team. We ask that candidates select the stream that best matches their experience and excitement.

Work Streams

Stream A: GPU Optimization & Training Performance

Maximize hardware utilization across 100B+ parameter asynchronous RL training runs. Responsibilities include profiling, performance optimization, custom kernel development, communication-computation overlap, and long-context throughput improvements. You set and maintain the performance baseline.

Stream B: Stack & Infrastructure

Own the post-training infrastructure end-to-end — supervised fine-tuning, asynchronous RL with tool integration, and data pipelines. Build modular, reproducible workflows with single-command execution. Manage upstream framework upgrades and deliver composable pipelines spanning Data, SFT, and RL stages. You work tightly with Research Scientists to develop and productionize novel algorithms to run at scale.

Stream C: Model Experimentation

Bring deep, hands-on experience training large language models. Lead experimentation on reasoning model development, including mixture-of-experts stabilization, curriculum design, and synthetic reasoning trace generation. You have a bias toward experimental design and tracking, and know how to prioritize runs that yield promising outcomes.

Stream D: Evaluations & Benchmarks

Design and build best-in-class scientific agentic benchmarks and harnesses, along with the dashboards and leaderboards that inform every training decision. You have experience working with well known public benchmarks and have spent time building bespoke agentic benchmarks and harnesses.

Stream E: Agentic Capabilities & Frontier Research

Train models capable of planning, exploration, and tool use over extended horizons. Advance the state of the art in RL at scale with tool-calling, subgoal decomposition, and shared memory/skills across trials to expand the frontier of scientific agent capabilities.

What You'll Need to Succeed

• Strong software engineering skills in Python; C++/CUDA a plus
• Experience with distributed ML training frameworks (Megatron-LM, TorchTitan, DeepSpeed, Ray)
• Understanding of large-scale model training techniques for 100B+ models
• Experience with cloud or HPC environment
• Ability to communicate technical results to internal and external stakeholders

Bonus Points For

• Prior work with large scale scientific datasets or domain-specific modeling
• Contributions to open-source ML frameworks
• Experience with RL post-training (RLHF, GRPO, tool-augmented RL)
• Experience training MoE architectures

Location

San Francisco, CA or Cambridge, MA (Remote, Hybrid, and On-Site available depending on team needs).

Your Impact at LILA

Lila is seeking a dedicated and skilled Research Associate, Protein Sciences to join our high through-put Cell-Free Expression platform. As a Research Associate, you will play a vital role in our interdisciplinary research efforts focused on building and automating artificial intelligence-driven processes across a variety of valuable applications.

What You'll Be Building

• Development and refinement of cell-free expression systems for efficient protein synthesis.
• Optimize conditions for high-yield and high-quality protein production
• Prepare media and solutions for cell culture and processing
• Perform molecular cloning, mutagenesis, and other genetic manipulation for strain development.
• Demonstrate proficiency in operating and utilizing liquid handlers and robotic systems for automated laboratory processes.
• Collaborate with biologists, machine learning scientists, software developers, and other engineers to develop and optimize AI-driven processes.
• Track and maintain excellent data records in formats amenable to computational workflows.
• Analyze and interpret experimental data, prepare technical reports, and present findings to internal teams and stakeholders.

What You’ll Need to Succeed

• A bachelor's or master's degree in biochemistry, molecular biology, biotechnology, biological engineering, chemical engineering, or a related field.
• 1-3 years of laboratory experience
• Experience with cell culture techniques, including growth, maintenance, and transformation, across a variety of cell lines
• Familiarity with plate-based assays
• Excellent attention to detail, organization, and communication

Bonus Points For

• Skilled in cloning, expression and optimization of protein
• Data analysis using relevant software (Python, R, or similar)
• Scripting for automation platforms

Your Impact at LILA

As a Robotics Scientist at Lila, you will lead the research and development of autonomous robotic systems that serve as the intelligent physical infrastructure of our scientific superintelligence platform. You’ll develop novel algorithms and deploy intelligent robotic solutions that interact seamlessly with human scientists and complex lab environments. Your work will accelerate our mission by enabling fully autonomous workflows for scientific discovery, combining cutting-edge robotics, machine learning, and systems engineering.

What You'll Be Building

• Design and develop autonomous robotic systems for transport and workcell operations, integrating advanced path planning, navigation, and motion planning algorithms
• Build production-grade mobile manipulation platforms leveraging ROS/ROS2 and modular robotic architectures
• Advance robotic perception by integrating sensing modalities such as 3D vision, LIDAR, and tactile sensors to enable robust, adaptable task execution
• Use simulation environments to model, test, and optimize task planning, scheduling, and robot behaviors in diverse lab scenarios
• Collaborate with AI, mechanical, and software engineering teams to translate theoretical robotics research into real-world autonomous systems

What You’ll Need to Succeed

• Ph.D. in Robotics, Computer Science, Mechanical/Electrical Engineering, or a related field, or equivalent research experience
• Expertise in motion planning, path planning, and navigation for manipulation and mobile robotics
• Proficiency with ROS/ROS2, C++, and Python, with hands-on experience building robotic systems in real-world environments
• Deep understanding of perception systems and sensor integration (e.g., camera, LIDAR, tactile sensors)
• Proven ability to take robotic systems from concept through to deployment

Bonus Points For

• Experience with dual-arm mobile manipulation systems or other high-DOF robotic platforms
• Familiarity with simulation tools such as Gazebo, Isaac Sim, or PyBullet
• Background in machine learning for perception, control, or adaptive planning
• Experience with real-time decision-making in human-robot collaboration scenarios
• Strong publication or patent record in robotics, autonomy, or perception

Your Impact at LILA

As a Robotics Scientist at Lila, you will lead the research and development of autonomous robotic systems that serve as the intelligent physical infrastructure of our scientific superintelligence platform. You’ll develop novel algorithms and deploy intelligent robotic solutions that interact seamlessly with human scientists and complex lab environments. Your work will accelerate our mission by enabling fully autonomous workflows for scientific discovery, combining cutting-edge robotics, machine learning, and systems engineering.

What You'll Be Building

• Pioneering approaches for precise and dexterous robotic manipulation that leverage foundation models, reinforcement learning, diffusion-based methods, and human guidance to enable adaptive and intelligent robotic systems capable of complex tasks across diverse scientific environments
• Developing novel human-robot interaction frameworks that incorporate imitation learning, and learning from human guidance, feedback, demonstrations and corrections, creating intelligent robotic agents that can seamlessly integrate with human scientific workflows and rapidly adapt to new experimental contexts
• Advancing dexterous manipulation research through cutting-edge machine learning approaches, including diffusion models and adaptive learning algorithms, that synthesize multi-modal sensing (tactile, visual, and language) to develop generative skill representation sand sophisticated motor learning policies for intelligent robotic systems
• Designing autonomous robotic systems with trust calibration mechanisms, enabling intelligent agents that can dynamically adjust their behaviors based on contextual information in complex scientific tasks

What You’ll Need to Succeed

• Ph.D. in Robotics, Machine Learning, Computer Science, or a related field with demonstrated expertise in foundation models for robotic learning
• Advanced proficiency in reinforcement learning, diffusion-based methods, imitation learning, and adaptive learning algorithms for robotic manipulation
• Expert-level experience with machine learning frameworks (PyTorch, TensorFlow) and deep learning architectures for developing foundation models, with specific expertise in diffusion-based generative models for robotics
• Proven track record of developing multi-modal perception systems integrating tactile, visual, language and other contextual sensing for intelligent robotic agents
• Strong publication record in robot learning, demonstrating innovative approaches to trust calibration, contextual learning, and generative robotic skill learning

Bonus Points For

• Research contributions to foundation models and diffusion methods in robotics
• Experience with large-scale machine learning model development, particularly generative and diffusion-based approaches
• Expertise in human-in-the-loop learning, correction-based training paradigms, and diffusion-guided skill transfer
• Demonstrated ability to translate theoretical machine learning research, especially diffusion and generative models, into practical robotic implementations

Your Impact at LILA

The Senior Director, Small Molecule Therapeutics will lead the biological evaluation and screening of small molecule therapeutics across Lila’s discovery platform. This leader will build and scale a world-class screening organization that translates AI-designed and robotically synthesized molecules into validated biological insights and therapeutic opportunities.

Working closely with Lila’s chemistry, automation, and AI/computational teams, this role will establish the biological screening infrastructure required to rapidly evaluate novel chemical matter. The Senior Director will design and deploy high-throughput and high-content screening strategies, build automated assay platforms, and develop innovative approaches to interrogate large chemical spaces.

This leader will play a critical role in shaping Lila’s small molecule discovery engine by integrating biology, automation, and data science into scalable discovery workflows that accelerate the identification of high-quality therapeutic candidates.

What You'll Be Building

• Build and lead Lila’s small molecule biology and screening organization, including hiring, mentoring, and developing a high-performing scientific team.
• Design and implement high-throughput and automated screening platforms to evaluate small molecules generated through Lila’s AI-driven chemistry and robotic synthesis systems.
• Develop and optimize biochemical, biophysical, and cell-based assays to identify and validate novel small molecule hits.
• Establish scalable automation-enabled workflows for assay execution, screening campaigns, and data generation.
• Lead the development and implementation of DNA-encoded library (DEL) screening strategies and downstream validation pipelines.
• Partner closely with chemistry, computational, and automation teams to integrate screening results with molecular design and synthesis efforts.
• Define and execute screening strategies for new therapeutic targets, including target validation, assay design, and hit identification.
• Oversee large-scale screening campaigns, including hit triage, orthogonal validation, and early mechanism-of-action studies.
• Implement data-driven approaches to analyze screening outputs and guide iterative molecule design.
• Establish best practices for screening data quality, reproducibility, and assay robustness.
• Collaborate across disciplines to translate screening hits into validated chemical starting points for therapeutic programs.

What You’ll Need to Succeed

• PhD in Molecular Biology, Chemical Biology, Pharmacology, Biochemistry, or a related scientific discipline with 12–15 years of experience in drug discovery, or MS/BS in a relevant scientific field with 15+ years of industry experience in small molecule drug discovery and screening.
• Demonstrated experience building and leading small molecule screening teams or platforms, including hiring, mentoring, and developing multidisciplinary scientists.
• Proven track record designing and executing high-throughput screening (HTS) campaigns for small molecule discovery.
• Deep expertise in biological assay development, including biochemical, biophysical, and cell-based assays used in early-stage drug discovery.
• Experience establishing automated or robotics-enabled laboratory platforms, including integration of liquid handling, assay automation, and scalable experimental workflows.
• Experience with DNA-encoded library (DEL) screening or other large-scale chemical library interrogation approaches.
• Strong understanding of hit identification, triage, and validation workflows in small molecule discovery programs.
• Experience working closely with medicinal chemistry teams to translate screening hits into validated chemical matter.
• Demonstrated ability to operate effectively in highly interdisciplinary environments spanning chemistry, biology, automation, and computational teams.
• Track record of scientific leadership and program delivery, including advancing discovery programs and mentoring scientific teams.

Bonus Points For

• Familiarity working in AI-enabled drug discovery environments or integrating machine learning insights into experimental workflows.
• Experience scaling automated discovery platforms that integrate robotics, high-throughput screening, and computational workflows.
• Deep familiarity with large-scale screening technologies, including DNA-encoded libraries (DEL), fragment screening, or other modern small molecule discovery approaches.
• Experience implementing high-content screening, phenotypic assays, or complex cellular screening systems.
• Strong understanding of screening data analysis and interpretation, including management of large experimental datasets.
• Experience building screening infrastructure from the ground up, including instrumentation selection, workflow design, and laboratory automation.
• Demonstrated ability to lead in fast-moving, innovative biotech environments.
• Strong communication skills and the ability to align multidisciplinary teams around ambitious scientific goals.

Your Impact at LILA

We are looking for a Program Lead to own the strategy and execution of our Life Science artificial intelligence science factory (AISF) Program. This is a single-point-of-accountability role: you will design and execute a plan that is maximally responsive to the priorities of the Product, Revenue, and Science teams while leveraging and extending the Lila tech stack. Success requires deep collaboration with stakeholders, representation of the strategy to the executive team, and driving progress via delegative leadership, where cross-functional Project Teams execute the strategy via our team-of-teams operating model.

Life Science AISFs span capabilities in cell biology, protein science, nucleic acid science, small molecule therapeutics, and targeted delivery — the experimental backbone that enables our AI to learn from biology at scale. This role sits at the intersection of deep domain expertise and strategic platform development, making it one of the most technically consequential leadership positions at Lila.

What You'll Be Building

Program Ownership

• Define the "How and When" in response to strategic "What and Why" inputs from Product, Science, and AI teams
• Propose, negotiate, and own Program Charters for Life Science AISFs, including scope, budget, timeline, and success criteria
• Collaborate with Finance to dynamically manage program budget and strategy throughout execution, escalating or reallocating as needed

Technical Leadership

• Architect the strategy for expanding Life Science AISF capabilities across cell, protein, nucleic acid, small molecule screening, and delivery experimental platforms, in close coordination with the Product, AISF Engineering, Software, Robotics, and Life Science Experiment teams
• Evaluate proof-of-concept results from frontier Science Programs (e.g., Autoimmunity, Solid Tumor, Protein Persistence), align with Product on their value creation potential, and design their integration into the Life Science AISF platform
• Ensure new platform capabilities are well-scoped, derisked, and positioned to accelerate downstream Intelligence Programs
• Maintain and extend Lila's best-in-world autonomous science platform for life sciences
• Design the Life Science AISF to be a maximally expressive lab with unprecedented responsiveness to AI guidance

Team and Execution Management

• Form and advise Life Science Project Teams; ensure teams have the resources, clarity, and support to execute autnomously
• Coordinate with Science Program Leads whose work depends on Life Science AISF capabilities
• Resolve resourcing conflicts within your program via collaboration with Product; escalate to senior leadership when a solution aligned to the approved charters cannot be identified

Stakeholder Communication

• Represent Life Science AISF programs in Technical Leadership Team (TLT) reviews
• Communicate program status, risks, and strategic decisions to TLT and cross-functional partners

What You’ll Need to Succeed

• PhD or equivalent experience in a life sciences discipline (cell biology, biochemistry, molecular biology, or related field), with substantial postdoctoral or industry research experience
• Track record of leading complex, multi-disciplinary experiment and lab automation programs
• Familiarity across multiple Life Science AISF domains (cell-based assays, protein characterization, nucleic acid workflows, or delivery systems)
• Experience with autonomous experiment platforms
• Experience defining and managing technical roadmaps with resource and timeline constraints
• Strong written and verbal communication, coupled with the ability to translate technical depth into strategic clarity for diverse audiences

Bonus Points For

• Familiarity with AI/ML-driven experimental design or closed-loop science workflows
• Prior experience in a fast-paced, technology-driven research environment (biotech, pharma, or deep-tech startup)
• Experience working in a matrixed organization with shared resources across multiple concurrent programs

Your Impact at LILA

What You'll Be Building

• Lead and build a high-performing team of senior scientists, scientists, and research associates focused on nucleic acid delivery technology development.
• Drive the discovery and engineering of targeted lipid nanoparticle systems for delivery of nucleic acid therapeutics.
• Design and evaluate targeting ligands, conjugation strategies, and nanoparticle architectures that enable tissue- and cell-specific delivery.
• Develop and implement innovative biological assays and screening platforms to evaluate delivery efficiency, biodistribution, cellular uptake, and functional nucleic acid expression or editing.
• Leverage the Lila AI platform and AI Science Factory to accelerate design–build–test–learn cycles through AI-driven experimental design and robotics-enabled experimentation.
• Collaborate closely with formulation scientists to integrate biological targeting strategies with lipid chemistry and nanoparticle formulation optimization.
• Explore and evaluate next-generation delivery modalities that extend beyond traditional LNPs.
• Establish strategic scientific direction for nucleic acid delivery research and ensure alignment with company-wide therapeutic goals.
• Foster a culture of innovation, collaboration, and scientific rigor, mentoring team members and developing future leaders in the field.

What You’ll Need to Succeed

• PhD in molecular biology, bioengineering, chemical biology, biomedical engineering, pharmacology, or a related discipline with 8–10+ years of relevant industry or academic experience, or a BS/MS with 12–15+ years of experience in nucleic acid delivery or genetic medicine.
• Demonstrated expertise in lipid nanoparticle technologies, nucleic acid delivery systems, or related genetic medicine platforms.
• Strong track record of scientific leadership and mentorship, including managing multidisciplinary research teams.
• Experience designing and executing in vitro and in vivo assays to measure delivery efficiency, biodistribution, and functional activity of nucleic acid therapeutics.
• Deep understanding of the biological mechanisms underlying delivery, including cellular uptake, endosomal escape, tissue targeting, and intracellular trafficking.
• Experience collaborating across disciplines including formulation chemistry, molecular biology, protein engineering, and pharmacology.
• Track record of impactful scientific contributions demonstrated through publications, patents, or therapeutic development programs.
• Excellent communication and strategic thinking skills with the ability to translate complex scientific ideas into actionable research programs.

Bonus Points For

• Direct experience developing targeted LNP systems or ligand-directed nanoparticle delivery technologies.
• Expertise in RNA therapeutics, gene editing systems (e.g., CRISPR/Cas), siRNA, mRNA, or DNA therapeutics.
• Experience integrating AI-driven discovery tools, high-throughput experimentation, or automated laboratory platforms into biological research.
• Experience working in highly collaborative environments spanning biology, chemistry, computational science, and engineering.
• Demonstrated ability to translate early discovery concepts into therapeutically relevant delivery platforms.
• Entrepreneurial mindset with a passion for pushing the boundaries of AI-enabled scientific discovery.

Your Impact at LILA

Lila Sciences is seeking an experienced Senior Research Associate specializing in Protein Purification, Analytics and Developability to support the build-out and day-to-day operation of a high-throughput protein characterization platform. In this role, you will contribute directly to the development of Lila's Scientific Superintelligence platform by executing and optimizing biophysical characterization workflows, collaborating effectively with cross-functional teams, and ensuring high-quality, reproducible data generation.

What You'll Be Building

• Execute and optimize high-throughput workflows for protein characterization across a wide range of modalities, including antibodies, bi-specifics, and enzymes.
• Operate and maintain automated chromatography systems, including Size Exclusion Chromatography (SEC), Hydrophobic Interaction Chromatography (HIC), and affinity chromatography using HPLC platforms.
• Perform biophysical characterization using techniques such as Dynamic Light Scattering (DLS), melting temperature analysis (DSF), binding assays (BLI/SPR), capillary electrophoresis (CE-SDS, cIEF) and more, to assess protein critical quality attributes
• Support workflows to characterize protein post-translational modifications (PTMs), ensuring comprehensive sample preparation and accurate data capture.
• Collaborate closely with scientists, engineers, and automation experts to identify and implement improvements in efficiency, robustness, and scalability of developability workflows.
• Innovate and adapt protocols to accommodate new protein formats, targets, and analytical strategies.
• Ensure data quality, documentation, and reproducibility in all experiments; actively contribute to knowledge sharing and continuous improvement initiatives.
• Collaborate with computational scientists to support data analysis pipelines, data processing, and the development of predictive models for protein characteristics.

What You’ll Need to Succeed

• Bachelor's or Master's degree in Biochemistry, Biophysics, Molecular Biology, Bioengineering, or a related discipline with 2-5+ years of hands-on industry or academic experience in protein production and characterization.
• Proven hands-on experience with HPLC techniques such as SEC, HIC, and affinity purification methods.
• Familiarity with biophysical characterization techniques including DLS, DSF, BLI/SPR, CE-SDS, cIEF or similar analytical methods.
• Experience with liquid handling automation and high-throughput formats.
• Familiarity with laboratory data analysis, digital recordkeeping (e.g., Benchling, electronic lab notebooks), and collaborative scientific workflows.
• Outstanding troubleshooting skills, adaptability, and ability to drive innovation in experimental design.
• Strong communication skills and an eagerness to collaborate within a fast-paced, cross-functional team.

Bonus Points For

• Familiarity with laboratory automation and high-throughput screening technologies.
• Data analysis using relevant software (Python, R, or similar).
• Experience with protein post-translational modification analysis workflows.

Your Impact at LILA

Lila Sciences is seeking an experienced Senior Research Associate to join our Antibody Platform team. In this role, you will play a pivotal role in building Lila's Scientific Superintelligence platform by leveraging your deep expertise in high-throughput antibody discovery, production, and characterization.

What You'll Be Building

• Design, optimize and execute high-throughput workflows for antibody expression and purification. Drive platform evolution by identifying opportunities to improve efficiency, robustness, and scalability of antibody production.
• Collaborate closely with scientists, engineers, and automation experts to discover, evaluate and implement novel automation tools, technologies, and reagents to expand the Antibody Platform’s capabilities.
• Innovate and adapt protocols to accommodate new antibody formats, targets, and expression strategies.
• Analyze antibody yield and binding characteristics using biolayer interferometry (BLI) and other relevant techniques; interpret and communicate findings effectively.
• Ensure data quality, documentation, and reproducibility in all experiments; actively contribute to knowledge sharing and continuous improvement initiatives. Collaboration, flexibility, and creative problem-solving are key to thrive in this dynamic role.

What You’ll Need to Succeed

• Bachelor’s or Master’s degree in Biochemistry, Molecular Biology, Bioengineering, or related discipline with 2–5+ years of hands-on industry or academic experience.
• Proficiency with antibody expression in CHO-S, including DNA transfection, small-scale cell culture, and antibody characterization; ExpiCHO expertise strongly preferred.
• Experience using sequence analysis software for molecular biology workflows and annotating antibody sequences, specifically Geneious, Benchling, PipeBio, etc.
• Experience with liquid handling automation and high-throughput formats.
• Experience with biolayer interferometry (BLI) or surface plasmon resonance (SPR) quantitative binding assays, CE-SDS, and antibody developability assays.
• Outstanding troubleshooting skills, adaptability, and ability to drive innovation in experimental design.
• Familiarity with laboratory data analysis, digital recordkeeping, and collaborative scientific workflows.
• Strong communication skills and an eagerness to collaborate with a fast-paced, cross-functional team.

Bonus Points For

• Skilled in cloning, expression and optimization of multispecific antibody formats
• Data analysis using relevant software (Python, R, Spotfire, or similar)
• Scripting for automation platforms

Your Impact at LILA

Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.  We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method.  We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at  www.lila.ai

At Lila, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way.

If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, please apply.

What You'll Be Building

• Agentic AI for science: Systems that perform sequential decision‑making and multi‑step reasoning to solve domain‑specific problems.
• Workflow/code generation: From natural language intent to typed, executable steps for lab instruments.
• Evaluation & reliability: Benchmarks, test suites, and telemetry to measure capability and quantify progress toward scientific goals.

What You’ll Need to Succeed

• PhD or Masters in a quantitative discipline (e.g., Computer Science, Physics, Mathematics, Engineering) with a strong background in machine learning and one domain of science (e.g. biology or materials science).
• Strong grasp of LLMs and agent architectures (planning, tool use, structured function calling, code generation) and how to adapt them to domains.
• Proficiency in modern ML frameworks (e.g., PyTorch, TensorFlow, JAX) and experience implementing scalable solutions for complex tasks.
• Comfort collaborating across disciplines and interfacing with simulations and real lab systems.

Bonus Points For 

• Building long‑horizon agents or RL for control/decision‑making; experience with model‑based or offline RL.
• Designing domain‑specific benchmarks and evaluation harnesses for complex scientific tasks.
• Digital‑twin development, calibration, and sim‑to‑real transfer.
• Publications or open‑source contributions in AI for science (especially publications in top-tier conferences like NeurIPS, ICML, AAAI, ICLR).

Location

San Francisco, CA or Cambridge, MA (Hybrid and On-Site available depending on team needs).

Your Impact at LILA

Lila Sciences is seeking an experienced Staff/Principal Mechanical Engineer to join our Hardware & Controls Engineering team. The specific title (Staff or Principal) will be determined based on experience level and expertise. As a key technical leader, you'll leverage your deep expertise to design and engineer components for workcell robotics, mechanical systems, and automation across life science and physical science domains. You'll collaborate with experimental scientists, AI/ML scientists, software/controls engineers, and process/automation engineers to lead complex projects, guide multidisciplinary teams, and deliver state-of-the-art automation solutions.

What You'll Be Building

• Lead the design and implementation of bench-scale robotics and mechanical systems for sophisticated automation in life science and physical science applications.
• Design innovative pneumatic, electro-mechanical, and optical solutions for advanced robotic workcells used in biological research and materials discovery.
• Lead and mentor teams in advanced CAD design and analysis using SolidWorks, optimizing systems for high-throughput workflows.
• Direct the creation and validation of designs through 3D printing, laser cutting, and other rapid prototyping methods.
• Lead cross-functional collaborations to integrate mechanical designs with software and controls across scientific domains.
• Develop strategies to transform manual processes into automated workflows while maintaining rigorous safety and quality standards.
• Coordinate with external vendors for custom component development and system integration.

What You’ll Need to Succeed

• Bachelor's or Master's degree in Mechanical Engineering, Robotics, or a related field.
• 8+ years of mechanical engineering experience with proven expertise in life science and physical science automation (title will be determined based on experience & expertise).
• Extensive proficiency in SolidWorks CAD design, GD&T, and DFMA
• Extensive proficiency working with & implementing requirement management systems, product lifecycle management, & product data management.
• Demonstrated leadership in managing complex projects and mentoring engineering teams.

Bonus Points For

• Deep experience in automation across scientific domains, with expertise in SolidWorks CAD design, PDM Vault management, rapid prototyping, and mechanical testing.
• Expert knowledge of motion control and mechatronic systems for diverse scientific applications.
• Strong background in automated systems and robotic integration for biological research, and materials science in the biotech sector.
• Demonstrated strong attention to detail in documentation, adherence to standards, and equipment management.
• Experience in automotive manufacturing, battery manufacturing, semiconductor manufacturing, and packaging with discrete material movement.

Your Impact at LILA

Lila is hiring a Boomi Developer to design, build, and support integrations that power our core business systems. You’ll own end-to-end integration delivery in Boomi AtomSphere—from requirements and mapping through deployment, monitoring, and ongoing support—partnering closely with Finance, People Ops, IT, and GTM stakeholders. Experience with procure-to-pay (P2P) and onboarding/offboarding workflows is a strong plus.

What You'll Be Building

• Design, develop, and maintain Boomi AtomSphere integrations (processes/atoms, APIs, schedules, connectors) across ERP, HCM, IAM, CRM, ITSM, and data platforms.
• Translate business requirements into scalable integration designs and data mappings (JSON, XML, CSV, EDI).
• Build resilient error handling, retries, and alerting; ensure observability and clear runbooks for L1/L2/L3 support.
• Manage Boomi MDH to support Data Quality and Source Data integrity
• Implement and manage REST/SOAP APIs, webhooks, and event-driven patterns where appropriate.
• Optimize existing integrations for performance, reliability, and cost; deprecate legacy jobs safely.
• Manage CI/CD, environment promotion, and release governance for integration assets.
• Ensure data quality, security, and compliance (PII handling, least privilege, audit readiness).
• Partner with stakeholders to prioritize a roadmap; provide estimates, status, and documentation.
• Provide production support within defined SLAs, including incident response and root-cause analysis.
• Contribute to standards, templates, and best practices for integration development at Lila.

What You’ll Need to Succeed

• 3–5 years in integrations/iPaaS, including 2+ years hands-on with Boomi AtomSphere.
• Proficiency with API design and integration (REST/SOAP), authentication (OAuth2, JWT, API keys), and data formats (JSON, XML, CSV).
• Strong data transformation skills (map functions, scripting, XSLT preferred) and error-handling patterns.
• Solid SQL fundamentals; familiarity with relational schemas and data modeling for integrations.
• Solid MDH experience
• Experience with Git-based workflows and CI/CD for integration deployments.
• Excellent collaboration and communication with non-technical stakeholders.

Bonus Points For

• Direct experience building/supporting Procure-to-Pay integrations (e.g., ERP, procurement, AP, payments).
• Direct experience with Onboarding/Offboarding integrations across HRIS, IAM/SSO (e.g., Okta/Azure AD), ITSM, and device management.
• Boomi certifications (Professional Developer, API Management, MDM) or equivalent.
• Familiarity with ERP (e.g., NetSuite/Oracle/SAP), HRIS (e.g., Workday/BambooHR), ITSM (e.g., Jira/ServiceNow), and procurement (e.g., Coupa).
• Experience with event-driven architectures, queues/streams (e.g., Kafka/SQS), and EDI B2B flows.
• Scripting for integrations (Groovy/JavaScript), and lightweight Python for tooling.
• Exposure to BOOMI AI functionality

Your Impact at LILA

The Director, Strategic Events will build and lead Lila’s global external events function. You will own a portfolio of high‑impact programs—flagship Lila events, executive summits, investor and partner gatherings, policy convenings, and key third‑party conferences—that drive pipeline, relationships, talent, and brand.

This is not a logistics planner role. You own the “why” and “how” of events: which audiences we prioritize, what we say, and how each moment advances Lila’s goals with:

• Investors – understanding our platform, business model, and roadmap
• Commercial partners & customers – seeing AISF capabilities and use cases, ssi milestones and team capabilities
• Policymakers – building trust in SSI, safety, and responsible deployment
• AI & science talent – experiencing our mission, culture, and technical ambition

What You'll Be Building

• Develop a 12–18 month strategic events roadmap aligned with company priorities and GTM motions (e.g., SLAS, JPM, NVIDIA GTC, Lila‑hosted summits, hackathons).
• Define clear objectives and KPIs for each event (pipeline and revenue influence, investor and partner meetings, policy relationships, talent leads, brand reach).
• Own strategy and execution for flagship and executive‑level events, including programming, formats, and audience journeys tailored for investors, partners/customers, policymakers, and technical talent.
• Lead cross‑functional planning with MarCom, Commercial, BizOps, Federal/Policy, Talent, and Science/AI/Robotics teams to ensure events are fully integrated with product, PR, content, and recruiting.
• Manage budgets, agencies, and vendors, including sponsorships and production partners, with clear forecasting and ROI tracking.
• Design immersive experiences and demos that bring Lila’s AI platform, AI science factories and scientific breakthroughs to life for different audiences.
• Build scalable playbooks and processes so future regional and functional teams can execute consistent, high‑quality events.

What You’ll Need to Succeed

• 10–15+ years in strategic events, event marketing, or experiential marketing, ideally in B2B tech, life sciences, or AI.
• Proven track record owning a global events portfolio that serves multiple senior audiences (investors, enterprise customers/partners, policymakers, technical communities).
• Strong program management skills and comfort operating in a fast‑moving, highly cross‑functional environment.
• Ability to define and track event ROI, working with CRM and marketing tools (e.g., Salesforce or equivalents).
• Excellent storytelling and communication, with the range to speak credibly to investors, scientists, engineers, policymakers, and candidates.
• Experience managing vendors and influencing C‑suite leaders.
• Willingness to travel 25–40% for events and on‑site execution.

Your Impact at LILA

Lila Sciences is seeking a highly skilled, hands-on Automated Systems Engineer to design, develop, and implement automation solutions across a broad range of laboratory workflows. Reporting to the Automated Systems Engineering Lead, this role is critical to building scalable, high-throughput automated workcells that translate scientific intent into reliable, real-world systems.

This role serves as a steward of scientific and cross-functional requirements—working closely with scientists, hardware, controls, and software teams to define scope, align interfaces, and drive projects from concept through deployment. The successful candidate will actively partner with scientific partners helping shape the technical direction of experimental automation in a fast-moving research environment.

What You'll Be Building

• Actively contribute to hands-on development, testing, and implementation of automated workflows in the lab.
• Develop scalable automated solutions for synthesis and characterization workflows, supporting a variety of material systems such as porous materials, catalysts, coatings, and advanced composites.
• Define and document standardized laboratory workflows, operating procedures, and system architectures to support reproducibility and scale.
• Lead and participate in equipment- and system-level FMEAs to improve robustness and operational safety.
• Assist in the troubleshooting and optimization of automated systems for throughput, reliability, and adaptability across diverse workflows.
• Design failure detection methods and maintain laboratory automation systems to ensure robust operations.

Project Innovation

• Translate scientific objectives into well-scoped technical requirements and automation architectures.
• Act as a connective tissue between science, hardware, controls, and software—ensuring interfaces are clear and solutions are cohesive.
• Explore and integrate emerging technologies, such machine vision, and advanced sensors, to enhance automation capabilities.
• Ensure alignment of automation solutions with safety, quality, and regulatory standards.

What You’ll Need to Succeed

• Strong hands-on experience developing and scaling automated workflows in laboratory or industrial settings.
• Understanding of Python programming, including API integration and error handling.
• Understanding of CAD design and rapid prototyping, including 3D printing.
• Hands-on experience with hardware systems, including electrical wiring, sensors, liquid/gas plumbing, and PID controllers.
• Strong critical thinking skills, attention to detail, and ability to work collaboratively in a dynamic environment.
• Excellent communication and interpersonal skills, with the ability to convey technical concepts clearly to diverse audiences.
• Familiarity with advanced experimental systems, including vacuum, laser, furnace, and electrochemical experimentation.
• Knowledge of machine vision applications and robotics control algorithms.
• Proven ability to integrate hardware and controls systems with automation workflows.
• Understanding of AI-driven decision-making in research automation.
• Prior experience leading technical teams in a fast-paced R&D environment.

Bonus Points For

Working at Lila Sciences, you would have access to advanced technology in the areas of:

• AI experimental design and simulation
• Automated custom instrumentation
• Generative molecular and material design

Your Impact at LILA

Lila Sciences is applying its autonomous science platform to some of the most complex challenges in biology and medicine — from protein therapeutics and nucleic acid design to antibody discovery and cell therapies. The Life Sciences experiment team is running programs where the pace of autonomous experimentation demands real operational rigor, and we're looking for a Technical Program Manager to provide it. You'll work closely with the Life Sciences domain lead who sets scientific strategy and direction, while you own the execution layer: the project plans, the cross-functional dependencies, and the blockers that need to be surfaced and resolved before they become problems. You won't be directing scientific work — you'll be creating the conditions for it to happen at speed and at scale. This is a role for someone who genuinely loves the craft of program management in complex, technical environments.

What You'll Be Building

• Own day-to-day program execution within the Life Sciences experiment team — maintaining project plans, tracking milestones, and ensuring agentic science programs are delivered on time and with rigor
• Serve as the primary operational interface between the Life Sciences team and platform partners (Automation, ML, Engineering) communicating needs, aligning on priorities, and keeping dependencies visible and resolved
• Translate scientific program goals into structured workstreams that enable autonomous experimentation to run efficiently and at scale
• Run program rituals including sprint planning, stand-ups, and retrospectives with a bias toward purposeful meetings, documentation, and follow-through
• Partner with the Life Sciences domain lead to surface blockers, risks, and interdependencies early and drive them to resolution
• Support the delivery of commercial contracts by working with the Product & Revenue team to ensure program commitments are well-scoped, tracked, and clearly communicated to all stakeholders
• Contribute to capacity planning and resource coordination in partnership with scientific leadership

What You’ll Need to Succeed

• 10+ years of program or project management experience in a life sciences or biotechnology environment
• A Bachelor’s degree in Life Sciences, Bioengineering, or a related field
• A track record of managing multiple concurrent programs in fast-paced, ambiguous environments and energized by building programs from the ground up; early-stage start-up experience is a strong plus
• Demonstrated ability to coordinate across scientific and operational stakeholders and manage complex cross-functional dependencies
• Sufficient scientific fluency to understand Life Sciences program goals and communicate them clearly to partner teams
• Experience supporting commercial program delivery and working with external partners or customers
• Exceptional written and verbal communication skills — able to break complex goals into clear, achievable units of work and keep stakeholders consistently well-informed

Bonus Points For

• Familiarity with project management tools such as Smartsheet, Asana, Jira, or similar
• PMP, PgMP, or agile certification (e.g., CSM, SAFe) is a plus

Your Impact at LILA

Lila Sciences is looking for an Associate Director / Director, Program Management, Life Sciences — a senior operator who will drive the planning, execution, and delivery of therapeutic programs on Lila's platform. This person will provide direct project management leadership to the internal science, engineering, and automation teams developing molecules for our partners, owning timelines, resourcing, and progress tracking across complex, multidisciplinary programs. They will also serve as a senior operational interface with our pharmaceutical and biotech partners, ensuring that deliverables, governance, and communication are running smoothly.

These programs carry significant scientific complexity and commercial stakes. This role requires someone who can drive execution across fast-moving, technically demanding programs from the inside while maintaining the partner-facing judgment and presence to keep external stakeholders informed and aligned.

What You'll Be Building

• Own end-to-end project management for active therapeutic programs, including timeline development, resource coordination, milestone tracking, and dependency management across product, science, machine learning and automation teams
• Drive day-to-day execution discipline; ensuring that internal teams have clear priorities, deliverables, and decision points, and that blockers are identified and resolved quickly
• Manage resource allocation discussions and trade-off decisions across a complex set of priorities (e.g., balancing experiments between AI model training and near-term partnership deliverables)
• Establish and maintain program-level reporting, including status updates, milestone tracking, and resource utilization views for internal leadership and external deliverables
• Proactively identify, communicate, and manage program risks, escalating appropriately and ensuring transparency with scientific and executive leadership
• Structure and facilitate effective internal program meetings, decision forums, and reviews; ensuring the right information reaches the right people at the right time

Partner-Facing Delivery

• Serve as the primary operational interface with partner organizations, coordinating joint governance, managing deliverable timelines, and driving alignment on milestones and expectations
• Translate internal program status into clear, structured updates for external partners, ensuring transparency without overexposing internal complexity
• Support alliance obligations including joint steering committees, milestone reporting, and deliverable handoffs
• Partner closely with scientific and product leadership to ensure that program plans reflect both Lila's platform capabilities and partner-specific program goals and business objectives

Process & Scale

• Lead the development of scalable project management practices, templates, and tools as Lila's partnership portfolio grows
• Help build repeatable operating models for how Lila plans, tracks, and delivers partner programs

What You’ll Need to Succeed

• 8+ years of experience in the pharmaceutical or biotechnology industry in roles associated with drug discovery or development, project management, or operations
• 5+ years in program management, project management, or a similar cross-functional coordination role with direct responsibility for timelines, resourcing, and tracking
• Demonstrated ability to independently drive execution across complex, multidisciplinary programs with significant scientific and commercial stakes
• Strong understanding of drug discovery and development processes; ability to engage credibly with scientific stakeholders and communicate at a high level across therapeutic and technical domains
• Experience managing programs with external partners, including milestone management, governance, and stakeholder communication
• Outstanding communication skills, with the ability to distill complex scientific and operational information for diverse audiences including executive leadership and external partners
• Proven ability to influence without authority and drive alignment across cross-functional teams

Bonus Points For

• Experience working at or partnering with AI-native or platform-based drug discovery companies
• Experience managing external collaborations in a discovery or preclinical setting (alliance management, CRO/CDMO oversight, or joint research programs)
• Familiarity with project management tools and methodologies (e.g., critical path analysis, scenario planning, resource management, portfolio reporting)
• Familiarity with the rapid evolution of LLMs and AI-driven science platforms and a perspective on how this will impact partnership models in drug discovery

Your Impact at LILA

We’re seeking a Head of Supply Chain & Strategic Sourcing to design and scale the function that keeps our scientific platform moving. You’ll own sourcing, procurement, vendor management, inventory, and payments with responsibility for hundreds of millions in annual spend across scientific equipment, lab operations, consumables, and technology infrastructure.

This role sits at the intersection of science, engineering, and finance. You’ll work closely with R&D, engineering, and AI research teams to ensure material availability, supplier performance, cost optimization, and operational resilience. If you’ve built procurement functions in environments where the stakes are high and the pace is fast whether in biotech, AI infrastructure, advanced materials, or hardware this is the role for you.

What You'll Be Building

• Design and scale the end-to-end Procure-to-Pay (P2P) process: sourcing strategy, purchasing channels, vendor governance, and payment operations.
• Lead strategic sourcing: supplier selection, contract negotiations, and ongoing vendor management.
• Build scalable supply chain infrastructure to support complex labs, capital equipment programs, specialized materials, and evolving R&D needs.
• Implement and optimize ERP/P2P systems, automation, and operations (procurement tools, AP workflows, controls).
• Create KPIs and dashboards to drive cost savings, supplier performance, and working capital optimization.
• Establish governance, policies, internal controls, and scalable systems for compliance and audit readiness.
• Centralize procurement operations to align purchasing, payments, leasing, and working capital management.

What You’ll Need to Succeed

• 10+ years of progressive leadership in procurement, supply chain, or P2P operations.
• Experience building or transforming supply chain/P2P in a high-growth setting.
• Experience in biotech, life sciences, AI, advanced materials, or hardware-enabled environments.
• Deep knowledge of ERP and procurement systems (examples: NetSuite, Coupa, Ariba, Ramp; familiarity with Prendo if applicable).
• Proven success negotiating complex supplier agreements and driving cost optimization.
• Experience leading cross-functional teams through rapid growth in spend and headcount.
• Experience implementing modern procurement or ERP systems to replace legacy infrastructure.
• Experience overseeing leasing and equipment financing aligned with capital strategy.

Bonus Points For

• Familiarity with public-company readiness, SOX compliance, and audit environments.
• Experience developing equipment leasing and financing strategies to optimize capital deployment and cash flow.
• Relevant certifications (e.g., MBA, CPIM, CPSM) or equivalent experience.

Your Impact at LILA

Your role in our Physical Sciences division will focus on designing and implementing state-of-the-art simulation approaches to model transport, kinetics, rare events, and reaction networks, and integrating them with AI-driven platforms for materials discovery. Your work will be integral to our efforts in predicting, designing, and controlling the behavior of complex materials and molecular systems, and their acceleration via agentic AI. You will partner with diverse teams at Lila, including machine learning experts working on scientific superintelligence and materials science experts performing real-world experiments.

What You'll Be Building

• Develop and extend molecular dynamics and Monte Carlo algorithms to capture rare events, non-equilibrium processes, transport phenomena, and mapping complex reaction networks.
• Build scalable simulation workflows that integrate statistical mechanics methods with machine learned interatomic potentials and agentic AI frameworks.
• Design methods for coupling dynamics simulations with experimental observables to enable closed-loop verification and discovery with automated labs.
• Collaborate with computational scientists, machine learning experts, and platform engineers to advance the fidelity and scalability of simulation-driven materials discovery.
• Establish reproducible, modular software pipelines for statistical mechanics and dynamics simulations that can be deployed on HPC and cloud-based infrastructure.

What You’ll Need to Succeed

• PhD or equivalent research/industry experience in Physics, Chemistry, Chemical Engineering, Mechanical Engineering, Applied Mathematics, or related fields.
• Strong background in statistical mechanics, free energy calculations, reaction mapping, non-equilibrium dynamics, and rare-event sampling.
• Demonstrated expertise with molecular dynamics, Monte Carlo, and/or kinetic simulation software and frameworks (LAMMPS, GROMACS, OpenMM, HOOMD, etc.).
• Solid programming skills and experience with scientific computing (Python, C/C++, MPI, CUDA, etc.).
• Experience running and automating simulations on HPC and/or cloud environments at scale.

Bonus Points For

• Strong publication record applying advanced statistical mechanics or dynamics simulations to molecular and materials systems, including but not limited to molecular/biomolecular systems and solid-state materials and interfaces.
• Prior work in coupling dynamics simulations with data-driven, AI-based, and/or agentic frameworks.
• Good familiarity with machine learning frameworks (PyTorch, JAX, TensorFlow, etc.)
• Prior experience working with machine learned interatomic potentials, including model training, fine-tuning, and data generation
• Worked closely with experimental teams to extract and corroborate experimental observables from dynamics simulations

Your Impact at LILA

As a ML Research Scientist - Multimodal Data Extraction, you will advance Lila’s vision of scientific superintelligence by developing foundation models that autonomously read, interpret, and structure scientific knowledge across text, images, and experimental data in the physical sciences. Your research will help unify the world’s scientific information into machine-understandable form, powering reasoning, prediction, and autonomous discovery across materials science and chemistry.

What You'll Be Building

• Research and develop AI systems that extract and structure knowledge from diverse scientific sources.
• Design and fine-tune large language, multi-modal and specialized models for factual, interpretable data extraction.
• Build scalable pipelines for unstructured and heterogeneous scientific data, integrating text, tables, and visuals.
• Collaborate with domain experts to align extracted data with real-world discovery workflows.
• Publish research that advances the state of the art in multimodal understanding and AI-driven knowledge extraction.

What You’ll Need to Succeed

• PhD (or equivalent research experience) in Computer Science, Chemistry, Materials Science, or related field.
• Expertise in machine learning, NLP, and vision–language modeling using PyTorch and Hugging Face Transformers.
• Proven ability to train, fine-tune, and evaluate LLMs and multimodal models for scientific data extraction.
• Strong understanding of data structures and representations used in the physical sciences.
• Demonstrated research impact through publications, preprints, or open-source work (e.g., NeurIPS, ICLR, ICML, ACL, EMNLP, Scientific Journals).

Bonus Points For

• Experience with multimodal fusion architectures and document-level understanding.
• Knowledge of scientific document parsing (OCR, table extraction, figure-caption linking).
• Familiarity with knowledge graph construction or reasoning systems for science.
• Experience with noisy or heterogeneous real-world scientific data.
• Collaborative mindset and passion for advancing AI in the physical sciences.

Your Impact at LILA

Are you a strategic social thinker who thrives at the intersection of science, technology, and community? We’re seeking a Community & Ecosystem Growth Strategist who blends social strategy, influencer relations, and hands-on community building to accelerate Lila’s executives and scientific leaders’ credibility and reach. You’ll grow high-quality networks across academia, industry, government, and frontier tech ecosystems, helping our leaders participate credibly in technical discourse and earn durable attention.

What You’ll Be Building

Executive presence and follower growth

• Design and execute growth plans for key executives’ social profiles (X, LinkedIn, Substack, and niche platforms).
• Grow audiences with high-quality followers: researchers, lab leaders, R&D decision-makers, open-source contributors, and public-sector stakeholders.
• Establish an “always-on” cadence: posts, replies, threads, commentary, and light community engagement that feels authentic and valuable.

Engagement in frontier technical communities

• Actively participate in discussions around AI-accelerated science, robotics, materials science, life science, chemistry, frontier tech, generative AI, and agentic science.
• Bring Lila into conversations in helpful, credible ways, even in skeptical or high-signal threads.

Influencer and network activation

• Cultivate relationships with credible creators and technical influencers across academia, industry, and government-adjacent networks.
• Orchestrate co-created moments: AMAs, roundtables, briefings, interviews, guest threads, and research spotlights that elevate Lila leaders.

Thought leadership enablement

• Ghostwrite or co-author with executives and technical leaders while preserving their voice and cadence.
• Coach leaders on engaging in replies and threads to build trust and depth, not hype.

Measurement, learning, and iteration

• Define and track meaningful metrics: follower quality, engagement depth, network effects, and relationship development.
• Test hypotheses, and continuously refine the playbook.

What You’ll Need to Succeed

• Proven track record of organically growing executive and brand followings in technical/scientific spaces.
• Strong writing and editorial judgment for technical audiences; ability to translate complex ideas into clear, credible content.
• Comfort engaging in public technical discourse, including disagreement and skepticism.
• Marketing fluency to align with brand and communications strategy, plus the independence to run social/community initiatives day to day.

Bonus Points For

• Existing networks across AI-for-science, robotics, open-source, academia, national labs, or government-adjacent science/tech communities.
• Experience supporting executives or founders as thought leaders (voice, cadence, engagement strategy).

Your Impact at LILA

Your Impact at LILA

Lila is building at the frontier of AI-driven science, and the quality of our team is the most important variable in our success. As Director of Talent Acquisition, you will lead a team of recruiters, sourcers, and TA Operations professionals maintaining a critically high talent bar across AI, Software, and Scientific hiring.

You will set the strategic direction for how Lila finds, attracts, and closes exceptional talent in some of the most competitive markets in the world, designing interview processes, developing bespoke sourcing strategies, and building the metrics infrastructure to track what's working. You will also coach and mentor your team, raising the overall craft of the function.

The right person is deeply curious about highly technical disciplines, well-networked across AI, Software, and Science talent communities, and driven to multiply the brilliance and culture of the company with every hire. You operate with high autonomy and are motivated by building a talent function that is itself a competitive advantage.

What You'll Be Building

• Lead and develop a team of recruiters, sourcers, and TA Operations professionals, setting high standards for performance, craft, and candidate experience
• Own full-cycle recruiting strategy across the entire company, scaling the organization across multiple technical disciplines, functions, and geographies
• Design and continuously improve interview processes, sourcing strategies, and closing approaches for highly technical and competitive roles
• Build and deploy AI-powered tools and custom sourcing methodologies that raise the ceiling on how Lila recruits, and socialize best practices up to and including the C-suite
• Build and manage recruiting metrics and reporting infrastructure to track pipeline health, conversion rates, time-to-fill, and quality of hire
• Serve as a thought partner to senior leadership on talent market trends, hiring forecasts, and team-building strategy

What You’ll Need to Succeed

• 10+ years of recruiting experience, with at least 3 years building and leading high-performing TA teams in a fast-growing company
• Demonstrated success developing recruiter capability, raising the bar on sourcing craft, candidate quality, and team-wide performance
• Deep technical recruiting expertise across multiple of the following: AI/ML, Software Engineering, Scientific research
• Proven ability to scale a recruiting function across disciplines, geographies, and role types as a company grows
• Track record of building and deploying AI-powered tools and custom sourcing methodologies that give the team a structural advantage
• Strong command of recruiting metrics and the ability to translate data into team priorities and hiring strategy
• Advises senior leadership and hiring managers on talent strategy and how to build world-class teams at scale

Bonus Points For

• Experience scaling TA functions at high-growth companies from early stage through significant organizational expansion
• Familiarity with the talent landscape in AI, biotech, or deep tech
• Experience recruiting internationally or building multi-region hiring pipelineS

Your Impact at LILA

We are seeking a highly organized and proactive Administrative Coordinator to provide operational and administrative support to our Government Affairs team in Washington, D.C. This role is the operational backbone of the team and ensuring the Government Affairs office can focus on its core efforts. The ideal candidate is a self-starter who thrives in a fast-paced, politically dynamic environment and exercises sound judgment and discretion at all times. This role requires 5 days a week in office in Washington, DC.

What You'll Be Building

GA Team Support 

• Manage scheduling for government affairs team, including scheduling meetings with Members of Congress, agency officials, and coalition partners
• Coordinate domestic and international travel logistics, including flights, hotels, ground transportation, and itineraries
• Prepare and process expense reports, invoices, and reimbursements in a timely manner
• Draft, proofread, and edit correspondence, briefing materials, talking points, and internal memos
• Anticipate executive needs and proactively handle administrative matters with minimal direction

Office Management

• Oversee day-to-day office operations, serving as the primary point of contact for building management, vendors, and service providers
• Manage office supply inventory, equipment maintenance, and facilities needs
• Onboard new team members, including coordinating workspace setup, badge access, and IT provisioning
• Maintain organized filing systems for legislative documents, regulatory filings, lobbying disclosures, and compliance records
• Coordinate with IT support to troubleshoot technology issues and manage software subscriptions

Legislative & Government Affairs Support 

• Assist with the preparation and timely filing of lobbying disclosure reports (LDA filings) in coordination with compliance counsel
• Maintain and update contact databases for congressional offices, agency contacts, and external stakeholders
• Coordinate logistics for Capitol Hill meetings, fly-ins, briefings, receptions, and fundraising events with external consultants
• Support the preparation of leave-behinds, one-pagers, and materials for Congressional meetings

Events & Stakeholder Coordination

• Plan and execute team events, including staff retreats, coalition meetings, roundtables, and receptions
• Manage coordination including invitations, RSVPs, catering, AV setup, and venue coordination
• Liaise with external partners, trade associations, and consulting firms on joint events and initiatives

What You’ll Need to Succeed

• 3–5 years of experience in an executive assistant, office manager, or administrative role, preferably in public service, government affairs, lobbying, law, or public policy environment
• Strong familiarity with the Washington, D.C. political landscape, including how Congress and federal agencies operate
• Exceptional organizational skills with the ability to manage multiple priorities under tight deadlines
• Outstanding written and verbal communication skills
• High degree of professionalism, discretion, and judgment when handling sensitive or confidential information
• Proficiency in Microsoft Office Suite (Outlook, Word, Excel, PowerPoint) and collaboration tools (e.g., Teams, Zoom, Slack)
• Ability to travel up to 10% of the calendar year, including international travel
• Ability to be in office 5 days a week in Washington, DC

Preferred

• Experience supporting C-suite executives or senior government officials
• Familiarity with Lobbying Disclosure Act (LDA) compliance and reporting requirements
  • Experience with stakeholder or contact management platforms (e.g., Quorum, Fireside, Salesforce)
  • Familiarity with political giving processes, including PAC administration, contribution tracking, and FEC reporting requirements
• Bachelor's degree in political science, public policy, communications, business, or a related field

Bonus Points For

• Discretion & Professionalism — Handles sensitive political and organizational information with the utmost confidentiality
• Proactive Problem-Solving — Anticipates issues and resolves them before they escalate
• Attention to Detail — Produces accurate, polished work products consistently
• Adaptability — Remains calm and effective in a dynamic, high-stakes environment
• Relationship Management — Builds trusted relationships with internal stakeholders, congressional staff, and external partners

Your Impact at LILA

Lila is building AI Science Factories (AISFs) — highly automated, AI-directed labs that generate the proprietary experimental data powering our AI platform. As we scale from one AISF to many, the operational infrastructure that keeps those factories running is a first-class strategic capability.

The Director of Lab Operations & Maintenance Management (LOMM) owns the physical and logistical foundation of Lila's science operations: consumables and reagent supply chains, equipment asset management, CMMS management, waste coordination, space readiness, preventative maintenance (PM), first response equipment/instrument demand maintenance, and multi-shift logistics continuity.

This role will build out and manage Lila's Maintenance Management (MM) function from the ground up — hiring the initial team, developing best practices, and establishing the operational handoff as we mature and scale.

But this role is as much about building these systems as running them — you'll define the LOMM operating model, lead its expansion to new sites, drive AI-enabled innovation in how we manage lab resources, and author the standards that travel with every AISF we open.

You'll operate as a recognized authority on lab operations within Lila, partnering directly with VPs and senior leaders across Autonomous Science Platform (ASP), Finance, EHS, and Facilities. You'll be a principal contributor to the Blueprint program — the global deployment framework that defines how Lila builds and runs AI Science Factories at scale.

What You'll Be Building

Lab Operations Strategy & Operating Model

• Define and own the LOMM operating model across Lila sites — from single-shift pilot to multi-site, continuous operations
• Establish the systems, org structure, staffing model, and governance framework that enable LOMM to scale reliably
• Set and track operational KPIs (inventory accuracy, stockout rate, PM scheduling compliance, asset data integrity, ticket resolution time); use data to drive structured improvement cycles and report trends to ASP leadership

Consumables, Reagents & Supply Chain

• Own end-to-end supply chain continuity for all lab consumables, reagents, and PPE across all shifts and sites
• Design and govern the par-level inventory system, reorder triggers, cold storage management, and expiry tracking infrastructure
• Lead dual-source qualification strategy for high-risk consumables; build the satellite site supply chain playbook for future AISFs in support of the Blueprint project

CMMS & Equipment Asset Management

• Own CMMS strategy, selection, implementation, and long-term governance — accountable for data accuracy across all commissioned instruments and mobile assets
• Define asset tagging standards and location tracking protocols in alignment with Blueprint's asset taxonomy
• Own PM coordination across sites; ensure calibration access and instrument readiness for production operations

Maintenance Management— Build & Oversight

• Build out the Maintenance Management function from scratch in collaboration with Hardware & Controls Engineering (HCE) team: define the team structure, hire initial MM staff, and establish the operating model for instrument PM, calibration, and first-response troubleshooting
• Stand up a dedicated L1 (Level 1) maintenance support team as the first line of response for lab-floor issues across shifts: triage incoming requests, execute standard work (resets, swaps, basic mechanical/electrical checks, consumables replenishment for instruments as defined), and escalate efficiently to HCE- L2/L3 Sustaining Engineering, vendors, or Integration Automation Engineering when deeper troubleshooting or design changes are required
• Establish the escalation and handoff protocols between MM, LabOps, Research Operations (production team), and HCE/Automation; define the boundary between maintenance of commissioned instruments that are best serviced by MM and engineering modifications
• Explore and define the HCE onboarding/training model for MM technicians, including potential rotational program for cross-training and augmentation

AI Integration & Continuous Improvement

• Lead Lila's thinking on AI-enabled lab operations — evaluate, pilot, and scale intelligent solutions across inventory management, predictive reordering, asset tracking, and operational reporting
• Build a continuous improvement culture within LOMM: baseline metrics, run structured improvement cycles, and bring external best practices from the biotech/life sciences industry into Lila's operating model
• Define the innovation roadmap for LOMM in partnership with engineering and operations teams

Vendor & Logistics Management

• Own vendor relationships for all lab supplies and logistics within approved frameworks; partner with Finance on contract strategy for key suppliers
• Oversee lab-side receiving, intake, space readiness for new instrument deployments, waste and hazmat scheduling, gas management, and cold storage operations
• Manage LOMM support ticket system as the single intake for all lab supply, equipment, and space requests

Team Leadership

• Lead, grow, and develop the LOMM team across shifts and sites, scaling with each new site and shift expansion
• Build and lead the MM team as a direct report function — from first hire through a fully operational multi-site MM capability
• Define staffing models, hiring roadmaps, and capability development plans for both functions as they mature
• Build a team culture defined by operational rigor, proactive problem-solving, and continuous improvement

Blueprint Contribution & Multi-Site Scaling

• Author and own the LOMM chapter of Blueprint — documenting processes, system requirements, staffing models, and vendor frameworks so LOMM scales reliably to every new AISF
• Pilot the Site Launch Readiness Scorecard for each new facility; feed findings back into Blueprint standards
• Define the LOMM readiness criteria and pre-commissioning checklist for all future site launches

What You’ll Need to Succeed

• 12–15+ years of lab operations experience in a biotech or life sciences environment, with demonstrated strategic impact at the program or portfolio level
• Proven track record of defining and scaling lab operations systems — not just inheriting and running them; you've built operating models, established governance, and led functions through significant growth
• Deep expertise in CMMS selection, implementation, and governance — you've owned platform decisions and data accuracy programs, not just used the tool
• Experience building and leading teams across multiple functions, shifts, or sites — including hiring from scratch and developing operational capability in parallel with day-to-day execution
• Experience owning and successfully defending ISO 9001:2015 audits related to preventive maintenance (PM) and calibration programs (e.g., evidence packages, CAPAs, and auditor-facing readiness)
• Recognized as an authority in lab operations within your organization; comfortable operating as a peer to VPs and senior leaders and representing your function externally
• Strong strategic and systems-level thinking — you anticipate org-wide operational challenges and define the structures to solve them, not just the immediate fix

Bonus Points For

• Experience building or overseeing a Maintenance Management or instrument PM function — familiarity with IQ/OQ/PQ, calibration registries, MTBF tracking, and service vendor management
• Experience leading or partnering closely with field service / technical service teams (dispatch, SLAs, escalation models, parts logistics, and service performance management) in high-uptime environments
• Experience applying AI or intelligent automation to lab operations workflows (e.g., predictive inventory, automated asset tracking, AI-assisted reporting)
• Background in materials science, life science, and chemistry lab environments — familiarity with the specific consumables, reagents, handling requirements, and vendor landscape in those domains
• Experience supporting multi-shift or 24/7 lab operations
• Familiarity with QMS-adjacent environments (SOP document control, change control, training records)
• Experience contributing to a global site deployment or standardization program (playbook authorship, site launch readiness frameworks)

Your Impact at LILA

Lila Sciences is looking for a Director of Federal Strategy & Capture to convert senior agency relationships and deep policy fluency into real government partnerships and funding wins. This role sits within our Government Partnerships organization and operates at the front end of capture — shaping the competitive environment before opportunities are formally announced, reading where the federal funding landscape is heading, and opening doors that demand genuine scientific and policy credibility.

This is not a policy role. It's a capture role that requires someone with unusually deep federal experience.

What You'll Be Building

Named Account Ownership — Build, manage, and advance senior relationships at DOE, ARPA-E, NIH, and adjacent US mission agencies. You own the health, depth, and trajectory of those relationships over time.

Opportunity Shaping — Engage agencies early enough to influence how funding opportunities are scoped and structured before they become RFPs, ensuring alignment with Lila's strategic roadmap.

Cross-Agency Narrative Development — Partner with the Head of Government Partnerships to connect Lila's portfolio to national science priorities and build a prioritized federal pipeline.

Institution Building — Help stand up Lila's federal capture function, including how we track relationships, manage pipeline, and engage agencies systematically over time.

What You’ll Need to Succeed

• Senior US federal experience at the intersection of science, policy, and strategy — agency, NSC, interagency, or equivalent background
• Scientific fluency in life sciences, biotechnology, or adjacent domains
• A demonstrated track record of turning relationships into concrete outcomes: funded programs, formal partnerships, or procurement pathways
• Experience standing up new government functions, programs, or divisions from scratch
• Comfort operating in a fast-moving, resource-constrained environment where you're building as you go

Bonus Points For

• Familiarity with federal funding mechanisms — OTAs, cooperative agreements, SBIRs, BAAs — and how to position a company advantageously within each
• Existing relationships within DOE, ARPA-E, DARPA, BARDA, DoD, NSC, or interagency bioeconomy and biosecurity networks
• Experience working with or inside a startup, venture-backed company, or other resource-constrained private sector environment
• Familiarity with Congressional authorization and appropriations processes as they relate to agency R&D priorities
• Comfort with CRM or pipeline tracking tools to systematize relationship and opportunity management

Your Impact at LILA

What You'll Be Building

• Developing, wrapping, and adapting domain-specific tools for molecular modeling, data analysis, process optimization, molecular modeling, and more
• Deploying custom, agentic scientific workflows that integrate with industrial instruments (PLCs, control software) and data systems (ERP, MES, SCADA)
• Building real-time data pipelines that transform messy scientific data into actionable insights
• Creating intuitive interfaces that make complex AI/ML capabilities accessible to scientists
• Architecting solutions that scale from proof-of-concept to enterprise-wide deployment

What You'll Need to Succeed

• Background in biology, molecular science, or related scientific field
• Outstanding communication skills—you'll interface directly with both executives and the manufacturing line
• Experience with data engineering, ETL pipelines, and working with complex/messy datasets
• Strong full-stack development skills with the ability to work across backend, frontend, and data layers
• Exceptional problem-solving abilities and comfort with ambiguous requirements
• Knack for product discovery and ability to pass requirements back to the platform
• Willingness to travel to customer sites for frequent and extended deployments

Bonus Points For

• Previous customer-facing or consulting experience
• Depth in controls engineering and machine learning
• Experience with scientific computing libraries (NumPy, Pandas, SciPy, RDKit)
• Familiarity with ML/AI implementation and deployment
• Familiarity with modern web technologies (TypeScript, React)

What Makes a Great FDE

• Customer Obsessed: You're energized by understanding customer problems deeply and seeing your solutions drive real impact
• Fast Learner: You quickly grasp new scientific domains and translate complex requirements into elegant solutions
• Autonomous: You thrive with minimal supervision and take extreme ownership of customer success
• Collaborative: You work seamlessly with both technical and non-technical stakeholders
• Technically Versatile: You're comfortable jumping between technologies and picking up new tools as needed

Ready to Transform Scientific Discovery?

If you're excited about embedding with world-class scientists, shipping impactful solutions at startup speed, and building the future of scientific software, we want to hear from you. Join us in our mission to accelerate breakthrough discoveries that will define the next century of human progress.

Your Impact at LILA

As a Senior Accountant at Lila, you'll play a pivotal role in scaling and refining our financial operations during a period of rapid growth and innovation. You'll own core accounting functions, help implement best-in-class processes, and ensure timely, accurate financial reporting across the company. Partnering closely with Finance, Operations, and cross-functional teams, you'll bring rigor, insight, and systems thinking to support strategic decisions and maintain financial excellence. This is a high-impact opportunity to build and scale the accounting foundation of a company redefining the future of science.

What You'll Be Building

• Support the month-end close process, including preparing journal entries, reconciliations, and reporting
• Ensure accurate application of US GAAP, especially around fixed assets and leases
• Partner with lab ops, procurement, and other departments on fixed asset and lease workflows, tracking, and accounting
• Support audits and compliance efforts, including preparation of schedules and coordination with external auditors
• Drive improvements in accounting systems and processes (e.g., ERP optimization, automation of reconciliations)

What You’ll Need to Succeed

• CPA license
• Bachelor's degree in Accounting, Finance, or related field
• 4+ years of accounting experience, with at least 2 years in public accounting or a high-growth tech/life sciences company
• Strong knowledge of US GAAP
• Experience with accounting systems (e.g., NetSuite or similar ERP)
• Advanced Excel skills and a high degree of attention to detail

Bonus Points For

• Experience with Fixed Asset Accounting, Lease Accounting (ASC 842)
• Familiarity with internal controls and SOX compliance
• Exposure to FP&A or cross-functional business partnering
• Passion for Lila's mission and eagerness to support science at the cutting edge

Your Impact at LILA

Role will lead development and validation of novel mammalian cell based pooled assays. The role will span proof of concept to automated screens to generate highly multiplexed and high dimensional datasets. The role will partner across cell biology, protein design and nucleic acid teams to support biologic development programs with the rapid determination of binding, stability, function, and immunogenicity of a variety of biologics.

What You'll Be Building

• Build next-generation mammalian display based binding, stability, function, and immunogenicity assays.
• Implement state-of-the art multiomic, single cell and in situ sequencing workflows to create novel highly multiplexed assays.
• Partner with protein design, nucleic acid, protein and automation teams to apply these workflows to the development of biologics.
• Closed-Loop Experimentation and Execution: partner closely with engineering and automation to design and exercise platforms for automated, high-throughput experimentation and data-rich workflows. Collaborate with AI team to run iterative experiments in real time, enabling fast optimization and discovery cycles.
• Collaborate, Lead & communicate: Work with cell biologists, synthetic biologists, automation engineers, protein design scientists and data scientists to document systems, share insights, and refine best practices in autonomous science. Mentor junior scientists, align milestones with internal/external collaborators, contribute to IP and publications, and present findings across the org.

What You’ll Need to Succeed

• Ph.D. in Chemical/Biomedical Engineering, Biochemistry, Pharmaceutical Sciences, Immunology, or related field (or M.S./B.S. with 5–8+ years relevant industry experience).
• Expertise with the development and/or application of mammalian display or similar pooled mammalian (perturb-seq, MPRA, etc.) systems
• Expertise with designing, executing and analyzing single cell, in situ or multiomic sequencing based experiments
• Experience designing novel single cell, in situ or multiomic sequencing based techniques
• Experience designing, executing and analyzing flow cytometry and sorting based experiments
• Experience creating highly complex libraries of defined sequences in mammalian cells
• Experience designing, executing and analyzing NGS based experiments

Bonus Points For

• Experience with antibody or cell therapy development
• Imaging experience
• Experience with optical pooled screening or image-based cell sorting
• Experience with encapsulation/droplet/bead/microwell based antibody or cell screening

Your Impact at LILA

We’re seeking a Vice President / Head of Marketing focused on accelerating commercial growth and strategic partnerships. This role fuels pipeline, enables revenue, and increases partner-driven adoption across priority industry segments. Reporting line is flexible and can sit under our Chief Communication and works directly with the CEO/Founder, with day-to-day collaboration across Sales, Partnerships, Revenue, Product, and Scientific leadership. You will define and execute marketing motions that translate frontier science and technical capabilities into enterprise-ready programs that open doors, build trust, and close.

What You'll Be Building

Drive commercial demand and pipeline

• Build and run an integrated demand engine targeting senior scientific and business buyers (R&D leadership, innovation executives, technical decision-makers).
• Develop account-based marketing programs for enterprise and strategic accounts.
• Plan and optimize channel mix across digital, field events, executive programs, and partner-led efforts.
• Own reporting and iteration loops that connect marketing activity to pipeline outcomes.

Enable partnerships and ecosystem growth

• Create go-to-market motions with partners that generate qualified introductions and joint opportunities.
• Develop partner-facing materials, co-marketing kits, and joint event strategies.
• Identify and cultivate ecosystems that matter to LILA’s commercial expansion (scientific communities, industry networks, and mission-aligned institutions).

Build segment-specific positioning and sales enablement

• Translate LILA’s technical platform into clear, differentiated value propositions for priority verticals.
• Partner with Commercial leadership to define ICPs, buyer personas, and qualification narratives.
• Deliver sales enablement: pitch narratives, technical collateral, case studies, ROI framing, objection handling, and competitive context.
• Support longer enterprise sales cycles with the right proof points at each stage.

Produce content that supports revenue and credibility

• Develop high-leverage content (technical briefs, case studies, webinars, white papers, executive narratives).
• Package customer and partner outcomes into reusable assets that accelerate trust and decision-making.
• Ensure marketing outputs are consistent with LILA’s brand and narrative, in close coordination with Corporate Communications.

What success looks like (first 6–12 months)

• Clear commercial messaging and a repeatable set of sales assets for core segments.
• A measurable pipeline contribution engine tied to specific commercial targets.
• Partner co-marketing motions that produce qualified opportunities.
• A content and events strategy that materially improves credibility with enterprise scientific buyers.

What You’ll Need to Succeed

• 10+ years in B2B marketing, with senior leadership experience in high-consideration enterprise or technical markets.
• Track record of driving pipeline and revenue outcomes (demand gen, ABM, field marketing, partner marketing).
• Strong product/segment marketing instincts for complex technical products (AI, deep tech, SaaS, biotech, industrial tech).
• Ability to work fluently with technical teams and translate technical truth into buyer-relevant value.
• Experience building functions and operating systems from early stage to scale.
• Strong analytical and operational discipline, with comfort owning metrics and performance reviews.
• Collaborative leadership style with a high degree of ownership.

Bonus Points For

• Experience in vendor/partner ecosystems, or experience scaling marketing in AI-for-science contexts.
• Background in academic or research-domain communications, or with PhD communities.

Your Impact at LILA

Lila is looking for an HR Manager to join the HRBP team and serve as a reliable, day-to-day people partner to assigned managers and client groups. You will support the execution of people programs, help managers navigate employee relations and performance topics, and contribute to building a strong, consistent culture as the organization scales. This role is a strong foundation for growing into a broader strategic HR advisory capacity over time.

What You'll Be Building

• Partner with assigned managers to provide hands-on HR guidance on talent management, employee relations, performance management, and team effectiveness
• Coach managers on people leadership, navigating difficult conversations, and developing their teams
• Drive execution of core HR programs including performance review cycles, compensation planning, and engagement initiatives
• Identify trends in people data and employee feedback to surface insights and flag areas requiring attention
• Collaborate cross-functionally with HR, Legal, and Finance to ensure consistency and compliance across people processes

What You’ll Need to Succeed

• 5–7 years of progressive HR experience, with at least 2 years in an HRBP, HR generalist, or client-facing HR role
• Demonstrated ability to build trusted relationships with managers and leaders across an organization
• Solid knowledge of core HR disciplines including performance management and employment law fundamentals
• Experience coaching managers through complex or sensitive people situations
• Comfort operating in a fast-paced, evolving environment where priorities shift quickly
• Strong judgment and discretion when handling confidential matters

Bonus Points For

• Experience supporting technical or scientific organizations, particularly in biotech, AI, or deeptech
• Familiarity with HRIS and people tools such as HiBob, Udemy, Greenhouse, or similar platforms
• Background in organizational development, change management, or culture-building initiatives
• Experience in a startup or high-growth company where HR processes and infrastructure were still being built
• Comfort using AI tools to improve and scale people processes and programs

Your Impact at LILA

We are seeking a (Senior) Research Associate to join our Life Sciences team. This role will focus on formulating lipid nanoparticles (LNPs), functionalizing them with targeting ligands, and characterizing the resulting targeted LNPs (tLNPs). The ideal candidate will have hands-on expertise in LNP formulation and characterization, bioconjugation, protein characterization, and automation technologies. Your work will unlock new understandings in the delivery space by enabling a high-throughput closed-loop screening cascade for tLNPs. This position will work closely with others across the protein, cell biology, automation, chemistry machine learning, and data science teams to help establish high-throughput next-generation tools for targeted nucleic acid delivery.

What You'll Be Building

• Design, execute, and characterize (DLS, ribogreen, TNS, etc.) LNP formulations across multiple scales and mixing modalities
• Develop and refine high-throughput ligand conjugation and purification methods, employing automation and robotics to increase throughput
• Collaborate with cell assay and antibody specialists to screen hits across a variety of tissue targets in in vivo models
• Collaborate with chemists, biologists, engineers, and data scientists to document systems, share insights, and refine best practices in autonomous flow chemistry
• Write, implement, and maintain Standard Operating Procedures (SOPs) for both existing and new lab processes

What You’ll Need to Succeed

• MSc in Chemical Engineering, Biomedical Engineering, Pharmaceutical Sciences, or a related field with 3+ years, or BSc with 5+ years, of hands-on experience in targeted LNP production, or related experience. Industry experience strongly preferred
• Strong working knowledge of bioanalytical techniques (e.g., DLS, fluorescence spectroscopy, electrophoresis, in vitro assays)
• Experience with protein and antibody design and characterization
• Familiarity with automation and high-throughput workflows
• Excellent troubleshooting, communication and collaboration skills, with a proven ability to work effectively across interdisciplinary teams

Your Impact at LILA

Your role in our Physical Sciences division will center on developing the next generation of in silico materials discovery methods, from creating autonomous workflows and data-driven pipelines to building the interface between simulation and AI. You’ll pioneer strategies that enable agents to reason over simulation data, extract latent insights, and guide hypothesis generation and materials design. Your work will expand how we leverage simulation outputs for discovery, accelerating the integration of physics-based modeling and AI reasoning systems. You’ll collaborate with experts in areas spanning simulation, AI agents, and experimental automation to push the boundaries of digital discovery.

What You'll Be Building

• Develop methods and workflows for in silico materials discovery that connect physics-based simulations, generative models, and agentic AI systems.
• Build intelligent pipelines where AI agents can design, launch, interpret, and refine simulations autonomously.
• Design frameworks that utilize simulation data more effectively for prediction, inference, and discovery, including automatic feature extraction, model training, and data-driven exploration.
• Prototype and evaluate new paradigms for simulation-aware agents that can learn from and act on scientific simulations.
• Design data representations, metadata standards, and APIs that enable seamless flow of information between simulations, machine learning models, and experimental databases.
• Create scalable, modular workflows that bridge electronic structure, atomistic, and mesoscale simulations with AI-driven reasoning and hypothesis generation.
• Collaborate with computational scientists, machine learning experts, and platform engineers to integrate in silico discovery pipelines into Lila’s broader scientific superintelligence ecosystem.

What You’ll Need to Succeed

• PhD or equivalent experience in Computer Science, Materials Science, Chemistry, Physics, Applied Mathematics, or related disciplines.
• Strong foundation in in silico materials discovery, computational materials modeling, and/or simulation workflow design.
• Familiarity with large language models and their application in scientific domains, and
• Experience building AI-driven or agentic workflows for scientific automation and discovery.
• Solid programming skills in Python and scientific computing frameworks
• Familiarity with atomistic simulation software and libraries (e.g., VASP, LAMMPS, ASE, Pymatgen, etc.).

Bonus Points For

• Strong publication record in in silico materials discovery, simulation-AI integration, AI-driven inverse design.
• Familiarity with scientific agent architectures, large-scale reasoning systems, or multi-agent frameworks for hypothesis generation and experimental planning.
• Familiarity with ontologies, metadata standards, and data infrastructure for scientific simulations.
• Experience with automated experiment–simulation loops, integrating computational predictions with robotic or cloud-based laboratory platforms.

Your Impact at LILA

We are seeking a detail-oriented and highly collaborative Revenue Manager to own the operational execution of revenue accounting for licensing, collaboration, and other complex revenue agreements. This role sits within the finance function and focuses on ensuring accurate, timely, and scalable revenue processes, partner reporting, and billing operations.

What You'll Be Building

Revenue Operations & Execution

• Own day-to-day revenue accounting operations for collaboration, licensing, and other revenue-generating agreements
• Translate contract terms into operational workflows for revenue recognition, billing, and reporting
• Ensure revenue is recorded accurately and consistently in accordance with established accounting policies

Contract Interpretation & Application

• Review revenue agreements and summarize key accounting and operational terms (e.g., billing triggers, milestones, deliverables)
• Apply ASC 606 principles to support proper treatment of revenue, in partnership with technical accounting where needed
• Serve as a bridge between technical accounting conclusions and operational execution

Close & Reporting

• Lead monthly and quarterly close activities for revenue, including journal entries and reconciliations
• Maintain supporting schedules and ensure completeness and accuracy of revenue balances
• Support financial reporting and audit requests with well-organized documentation

Partner Billing & Reporting

• Own invoicing, cash application, and partner reporting processes
• Ensure billing and reporting align with contractual terms and timelines
• Track and manage milestone billing, cost-sharing arrangements, and other variable components

Process Improvement & Systems

• Build and refine scalable processes for managing revenue
• Partner with systems teams to operationalize revenue workflows in ERP systems (e.g., NetSuite)
• Develop templates, trackers, and documentation to improve efficiency and reduce risk

Cross-Functional Coordination

• Partner closely with legal, FP&A, business development, and scientific teams to ensure alignment between contracts and execution
• Proactively identify gaps or ambiguities in agreements that could impact revenue operations

What You’ll Need to Succeed

• 6+ years of experience in accounting, with exposure to revenue recognition
• Strong working knowledge of ASC 606 and ability to apply it in practice
• Experience operationalizing revenue processes (billing, revenue tracking, reconciliations)
• Experience reviewing contracts and translating terms into accounting workflows
• Strong attention to detail and ability to manage multiple agreements simultaneously
• Excellent organizational and cross-functional communication skills

Bonus Points For

• Experience in biotech, life sciences, or deep tech environments
• Familiarity with collaboration agreements, licensing, milestone-based revenue, or cost-sharing arrangements
• Experience with NetSuite or similar ERP systems
• CPA
• Ability to operate in a fast-paced, evolving environment

Your Impact at LILA

Origins is Lila's company and asset creation arm, where Lila's partners can turn scientific vision into molecules, materials, and real-world ventures. As a Senior Associate on the Origins team, you will work directly with leadership to evaluate and advance scientific opportunities. You will build analytical frameworks, partner-facing materials, and financial models that underpin how we identify, structure, and pursue these opportunities. This is a high-impact, high-ownership role for a builder who thrives in ambiguity and wants to be close to consequential decisions at one of the most ambitious scientific companies in the world.

What You'll Be Building

• Build and maintain financial models and projections to evaluate scientific opportunities and inform decisions
• Develop partner-facing materials, presentations, and analyses to support external conversations and deal processes, working alongside leadership and external partners
• Evaluate opportunities in the context of Lila's platform, assessing scientific, commercial, and strategic fit
• Support structuring and execution of ventures from early-stage diligence through deal close
• Synthesize complex scientific and financial information into clear, decision-ready outputs for senior leadership
• Collaborate across Lila's scientific, finance, legal, and product/revenue teams to advance active opportunities

What You’ll Need to Succeed

• Typically 4-6 years of experience, with a background in investment banking, private equity, or growth equity, and subsequent experience in venture capital, a startup, or a similarly fast-paced environment
• Bachelor's degree in a scientific or engineering discipline, or equivalent technical training
• Strong financial modeling and analytical skills, with the ability to build models independently from scratch
• Demonstrated ability to produce high-quality partner-facing materials and executive presentations under tight timelines
• Comfortable working in ambiguity with limited oversight, and able to manage multiple workstreams simultaneously
• Strong written and verbal communication skills, with the ability to distill complex information for senior audiences

Bonus Points For

• Experience evaluating early-stage scientific or technology opportunities
• Familiarity with deep tech or life sciences sectors
• Ability to engage substantively with scientific concepts and translate them into business and financial terms
• Experience working directly with senior leadership in a high-growth or fast-paced environment
• Proficiency in tools such as Excel, PowerPoint, and data visualization platforms

AI Resident – 2026 Cohort

The AI Residency Program is a full-time research opportunity designed to bridge the gap between academic research and industry applications in AI for materials science. Residents will work closely with Lila scientists and engineers on high-impact, open-science projects, with the option to focus on either fundamental or applied research.

• Duration: 6–12 months (extension possible)
• Start Dates: First hires beginning January 2026, with rolling applications and additional intakes in Summer and Fall 2026
• Cohort Size: Small group of selected residents
• Mentorship: Pairing with technical mentors, feedback from cross-functional teams
• Resources: Access to proprietary datasets, high-performance compute, and Lila’s research infrastructure

Research areas include ML-accelerated simulations, Bayesian methods, representation learning, generative models, agentic science, and ML-driven automation.

Your Impact at Lila

The Lila Sciences AI Residency is a full-time research program at the intersection of artificial intelligence and materials science. As a resident, you'll join a cohort of researchers tackling open-ended scientific challenges alongside Lila’s world-class team of scientists and engineers. With access to proprietary datasets, high-performance compute infrastructure, and experienced mentors, you'll pursue ambitious research projects with both academic and real-world impact. Publishing is encouraged but not required — what matters most is pushing the frontier of scientific discovery.

What You'll Be Building

• Design and execute independent research projects in AI for materials science
• Collaborate with Lila scientists and engineers on cutting-edge, open-science initiatives
• Explore domains such as ML-accelerated simulations, Bayesian methods, representation learning, generative AI, agentic science, and ML-driven automation
• Contribute to collaborative team research and co-develop novel approaches to scientific discovery
• Share findings internally and externally; publications are welcome but not mandatory

What You’ll Need to Succeed

• Degree in Materials Science, Chemistry, Computer Science, AI/ML, Physics, Mathematics, or related field (Bachelor’s, Master’s, or PhD)
• Proficiency in Python and deep learning frameworks (e.g., PyTorch)
• Experience working with large-scale datasets or simulations
• Familiarity with modern AI/ML architectures and training techniques
• Strong research background, demonstrated through publications, thesis work, or open-source projects

Bonus Points For

• Prior work on ML applications in scientific domains (e.g., materials discovery, chemistry, simulations)
• Familiarity with Bayesian optimization, active learning, or generative models
• Experience in reinforcement learning or agent-based approaches to scientific reasoning
• Open-source contributions or collaborative research experience
• Strong communication and writing skills, especially for conveying complex scientific ideas

Your Impact at LILA

Join us in shaping the future of science! We are seeking a software engineer with a background in life sciences to join our data science team, where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. This role spans web services and data engineering, with a strong emphasis on Python development for scientific applications. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!

What You'll Be Building

• Participate in the entire software development life cycle, focusing on designing, implementing, and maintaining software services.
• Develop reusable code and libraries to improve efficiency and scalability.
• Align development with strategic goals, ensuring software supports broader organizational needs.
• Manage git repositories, team Jira board and Notion Hub, promote best practices, assist lab scientists with use of new tools, and foster a collaborative development culture.
• Work directly with scientists to identify gaps and unmet needs, develop tailored software solutions for data management, LIMS functionality, and data automation
• Support infrastructure as code and design efficient deployment strategies.
• Write clear, concise documentation for both engineers and end users.

What You’ll Need to Succeed

• Minimum of 2 years of experience writing software in a commercial setting.
• High-level proficiency in Python.
• Strong understanding of git best practices.
• Acute listening skills and patience to deeply understand user challenges.
• Experience implementing scalable software solutions.
• Excellent problem-solving skills and team-first mentality.
• Strong communication skills to effectively collaborate with team members and stakeholders.
• Energetic self-starter and independent thinker, with strong attention to detail.
• Eager to work with highly skilled and dynamic teams in a fast-paced, entrepreneurial, and technical setting.

Bonus Points For

• Background in biological sciences
• Familiarity with data science and ML libraries (pandas, numpy, scipy).
• Knowledge of modern developer tools (pydantic, pyright, uv).
• Understanding of Kubernetes, ArgoCD, and GitHub Actions.
• Familiarity with AWS fundamentals (e.g., RDS, EC2, S3, EKS).

Your Impact at LILA

We are seeking a Senior Software Engineer to join our Applied AI group and help build the next generation of our AI-driven scientific platform. In this role, you will design and optimize the backend systems, data pipelines, and AI integrations that power intelligent, data-driven applications. You’ll work at the intersection of backend engineering and machine learning, ensuring our platform seamlessly scales and supports cutting-edge applied AI techniques such as Retrieval-Augmented Generation (RAG), agentic AI, and large language model (LLM) integration.

This role is ideal for someone who thrives in bridging software engineering and applied AI—turning research into production-grade systems that drive real-world scientific discovery. If you are passionate about building performant, elegant systems that make AI useful and impactful, we would love to hear from you!

What You'll Be Building

• Applied AI Integration: Design and deploy backend services and data pipelines that directly support advanced AI applications, including LLMs, RAG, and agentic frameworks.
• API & Service Development: Build high-performance APIs and microservices that enable seamless integration between AI models, scientific tools, and user-facing applications.
• Data Pipeline Architecture: Architect and manage scalable pipelines capable of handling structured, unstructured, and vectorized data for AI/ML workloads.
• Database & Knowledge Systems: Implement and optimize SQL, NoSQL, and vector databases to support low-latency AI retrieval and inference workloads.
• Cloud & Infrastructure: Leverage AWS, Kubernetes, and infrastructure-as-code (Terraform/CloudFormation) to build robust, production-ready AI platforms.
• Performance & Reliability: Diagnose system bottlenecks, optimize for cost and speed, and ensure the reliability and fault-tolerance of AI-driven workflows.
• Collaboration: Partner with ML researchers, platform engineers, and scientists to translate models and algorithms into scalable, production-ready systems.

What You’ll Need to Succeed

• Educational Background: Bachelor’s or Master’s in Computer Science, Engineering, or a related field.
• Backend & Data Expertise: 7+ years of professional experience building and scaling production systems, including APIs, data pipelines, and distributed services.
• Programming Skills: Strong Python skills (FastAPI, Flask, Django), with solid experience in backend service development.
• Databases: Proven experience with SQL, NoSQL, and vector databases; skilled in schema design, indexing, and query optimization.
• Applied AI Systems: Hands-on experience integrating ML models or AI-driven workflows into production services.
• Cloud & DevOps: Proficiency with AWS, Docker/Kubernetes, CI/CD pipelines, and infrastructure-as-code.
• Communication & Problem-Solving: Ability to work cross-functionally with diverse teams and explain complex technical concepts to non-experts.

Bonus Points For

• Scientific & Data-Intensive Domains: Experience working with life sciences, materials sciences, or other research-heavy fields.
• Startup Experience: Comfort with fast-paced, iterative environments where impact and adaptability matter.

Your Impact at LILA

As Commercial Counsel (Director/Associate Director) at Lila Sciences, you will be a foundational member of the legal team, responsible for shaping and scaling legal capabilities in a fast-moving, frontier technology environment. This is a dynamic, high-ownership role focused on structuring and negotiating a wide array of commercial agreements, while also advising on legal and regulatory considerations surrounding artificial intelligence, scientific research, and cutting-edge technology development. You'll partner cross-functionally across science, engineering, business development, and operations to enable Lila’s mission to accelerate discovery with AI.

We're looking for an experienced, entrepreneurial attorney with 6–10 years of legal experience—someone who is excited to work at the intersection of law, AI, and science. You should thrive in environments that demand both precision and creativity, be comfortable navigating ambiguity, and bring a strong sense of judgment and empathy to collaborative problem-solving. If you're passionate about building scalable legal infrastructure, engaging deeply with novel technologies, and evolving the practice of law using AI, this is the role for you.

What You'll Be Building

• Draft, negotiate, and manage a broad range of commercial agreements (e.g., SaaS, IP licensing, vendor, partnership, and R&D collaboration contracts)
• Provide pragmatic legal counsel to internal stakeholders across the business, product, and science functions, balancing legal risk with strategic objectives
• Serve as a thought partner on regulatory and ethical considerations related to the use of AI in scientific and commercial contexts
• Help build scalable systems and workflows to streamline legal processes and amplify team impact using AI tools and automation
• Support strategic transactions and partnerships, rapidly developing expertise in new domains to ensure sound legal outcomes

What You’ll Need to Succeed

• J.D. and membership in at least one U.S. state bar in good standing
• 6+ years of legal experience, with substantial time in-house at a technology company
• Deep experience drafting and negotiating complex commercial contracts
• Familiarity with AI, SaaS, and/or scientific R&D business models
• Ability to operate independently, manage multiple priorities, and communicate effectively across technical and non-technical teams

Bonus Points For

• Enthusiasm for transforming legal practice through AI and data-driven tools
• Prior work involving export-controlled technologies or CFIUS considerations
• Experience supporting R&D teams in life sciences, materials, or climate-tech domains
• Comfort with technical subject matter and scientific research environments
• Track record of building legal infrastructure or scalable processes from scratch

Your Impact at LILA

We are seeking a Product Marketing Manager, Physical Sciences to lead go-to-market for Lila’s AI-driven materials and chemistry platform. You will operate at the convergence of:

• Physical science domains: catalysts, sorbents, coatings, LNPs, quantum and extreme-environment materials
• Autonomous experimentation: flow chemistry ecosystems, high-throughput electrocatalysis, advanced characterization workcells
• AI & modeling: property prediction, design spaces, Bayesian optimization, LLM-augmented optimization

Your mission is to translate this tech stack into clear narratives, compelling launches, and credible evidence that resonate with:

• Industrial R&D and technology leaders in energy, chemicals, and manufacturing
• Sustainability and advanced materials teams
• Strategic partners, national labs, and federal programs

What You'll Be Building

Go-To-Market Strategy & Launch

• Define and execute GTM plans for new physical science capabilities (e.g., catalyst discovery campaigns, LNP property prediction, flow-reactor–based optimization, sorbents and coatings workflows), translating technical milestones into compelling market moments with clear offers, timelines, and success metrics.
• Translate PS product milestones (new AISF demos, CLUE campaign results, partner-ready vignettes) into launch-ready packages, including positioning, messaging, collateral, and enablement assets.
• Align launches with priority commercial motions in physical sciences (Accelerated By Lila, Lila Superscientists, joint development, and agentic science offerings) to maximize adoption and impact.

Messaging & Positioning

• Craft crisp, value-based messaging that communicates how Lila’s platform accelerates:
  • Catalyst and materials discovery for green hydrogen and electrochemistry
  • LNP design and advanced materials development for transport and separations
  • Coatings, sorbents, and quantum/extreme-environment materials discovery
• Tailor narratives for R&D executives, technical experts, and corporate innovation/sustainability leaders, clearly differentiating Lila from traditional HTE vendors, point-solution AI tools, and CROs.

Content Creation

• Produce technical and visionary content, including:
  • Domain-focused one-pagers and solution briefs (electrocatalysis, LNPs, sorbents, coatings, quantum materials)
  • Case studies and vignettes that translate CLUE campaigns, flow cell workcells, and AISF demos into partner-ready slides and visuals
  • Executive decks for Chevron, Merck-style conversations, industry keynotes, and joint partner briefings
  • Website and industry-page copy for physical sciences, in collaboration with Brand, CSO Materials, and PS leads

Sales & Field Enablement

• Partner with Commercial and BD to deliver high-impact collateral for physical-science prospects:
  • Pitch decks and talk tracks linked to CLUE, flow chemistry, LNP, sorbents, and coatings capabilities
  • Competitive positioning and objection handling against AI-for-materials and automation players
  • Simple ROI/value frameworks (faster time to best-in-class catalysts, improved yields, fewer experiments, enhanced durability)
• Capture learnings from customer and partner meetings (e.g., Chevron, energy majors, OEMs, national labs) and feed them back into messaging and product feedback loops

Market Intelligence & Insight

• Monitor competitive landscape and adjacencies in AI-driven materials discovery, HTE vendors, simulation platforms, and industrial R&D digitization
• Synthesize customer signals from commercial conversations, conferences (e.g., GTC, sustainability/energy events), and federal initiatives to inform PS product and business-model decisions
• Help prioritize PS storytelling priorities for 2026 (e.g., CLUE results and green hydrogen, LNPs and targeted delivery, extreme-environment coatings, quantum materials) to drive revenue and partnerships

Evangelism & Representation

• Serve as a visible advocate for Lila’s physical sciences work, supporting researchers in events, webinars, and joint partner sessions
• Collaborate with MarCom on PR and thought leadership that highlights CLUE, AISF for flow chemistry, electrocatalysis, carbon capture sorbents, and advanced materials achievements

Bonus Points For

Education

• Bachelor’s or Master’s degree in Chemistry, Materials Science, Chemical Engineering, or a related field. PhD a plus.

Experience

• 5+ years in B2B SaaS or technical product marketing, ideally within lab informatics, scientific software, or AI/ML for physical sciences, energy, or advanced materials.

Technical Understanding

• Strong grasp of AI/ML applied to physical sciences (e.g., property prediction, generative models for materials, Bayesian optimization, simulation-driven design).
• Comfortable discussing catalysis, sorbents, coatings, or related domains, even if you are not the domain PI.

Storytelling & Communication

• Proven ability to translate complex technical data and workflows into accessible, precise, and compelling narratives for scientists and business stakeholders; strong writing portfolio a plus.

Collaboration

• Track record of partnering with Product, R&D, and Commercial teams; able to serve as a trusted thought partner to PS leaders and researchers.

Execution & Ownership

• Strong project management skills; capable of coordinating multiple GTM streams in parallel and delivering on deadlines tied to events, partner meetings, and internal milestones.

Startup Mindset

• Comfortable in a fast-moving, highly cross-functional environment where product, category, and business models are evolving.

Your Impact at LILA

We are seeking a creative and skilled Multimedia Specialist to join our team. This in-house role will serve as the go-to resource for basic design (slides, overviews, explainers), video production, photography, animation, and multimedia content creation.

At Lila, this role also supports a highly technical environment. The Multimedia Specialist should be comfortable engaging with science and engineering teams, quickly learning new concepts, and helping translate complex work into clear, compelling visuals and narrative content. A background in science, biology, AI, robotics, or software is a strong plus.

In addition to content creation, this role will help ensure our growing set of visual and multimedia assets are organized, archived, and easy to reuse across teams, including Sales Enablement, Commercial, Marketing & Communications, and scientific teams documenting discoveries and lab processes.

What You'll Be Building

Multimedia production (core)

• Create and produce engaging multimedia content, including videos, graphics, and animations, for various platforms.
• Capture and edit high-quality photographs and videos for promotional materials, internal communications, and social content.
• Manage end-to-end production from concept development to final delivery, including light coordination of timelines, reviews, and asset handoff.
• Stay current with industry trends and best practices in multimedia production.

Scientific + technical communication

• Partner with scientific, engineering, and product stakeholders to understand complex topics and translate them into accurate visual stories.
• Produce content for both external-facing and internal audiences, such as:
  • Sales enablement and commercial materials (short videos, demo clips, slide visuals, one-pager graphics)
  • Scientific and technical explainers (animations, diagrams, process visuals)
  • Lab/team documentation that helps capture discoveries and workflows

Collaboration & visual storytelling

• Collaborate with Marketing & Communications team members to develop and execute visual storytelling strategies across channels.
• Work with cross-functional partners who need content daily, balancing speed with quality and consistency.

Content asset management & archiving

• Maintain an organized library of multimedia assets, including basic metadata/tagging, versioning, and archiving.
• Create lightweight norms/templates for naming conventions, file hygiene, and reuse so assets can be easily found and repurposed.

What You’ll Need to Succeed

• Minimum of 5 years of experience in multimedia production, with a strong portfolio showcasing your work.
• Proficiency in digital production tools, including but not limited to Adobe Creative Suite (Photoshop, Illustrator, Premiere Pro, After Effects).
• Excellent storytelling skills with the ability to create compelling narratives through visuals.
• Strong attention to detail, organizational skills, and ability to meet deadlines.
• Comfort working with scientists, researchers, and technical teams, including the ability to ask great questions and communicate clearly.

Bonus Points For

• Experience in a communications or digital marketing agency.
• Familiarity or comfort with scientific/technical topics. Background in science, biology, AI/ML, robotics, or software is a plus.

Your Impact at LILA

We are seeking a motivated and detail-oriented Senior Research Associate / Associate Scientist to join our high-throughput autonomous chemistry team. This is a hands-on role at the intersection of organic and inorganic synthesis, advanced characterization, and laboratory automation. You will design and execute high-throughput experiments, synthesize small molecules, and perform rigorous downstream analysis while working side-by-side with senior scientists to translate ambitious product goals into scalable experimental workflows that directly drive our company’s growth.

This position offers first-hand exposure to automated chemistry platforms, with real ownership over experiments that inform company strategy and scientific direction. Ideal candidates are execution-driven, thrive in fast-paced laboratory environments, and are eager to build deep technical expertise while contributing meaningfully to next-generation chemical discovery at Lila Sciences.

What You'll Be Building

• Independently execute experiments to synthesize, purify, and characterize organic and inorganic small molecules
• Optimize reactions, perform method development, and interpret analytical data to guide project decisions
• Translate early-stage ideas into reproducible, functional experiments
• Apply retrosynthetic planning to support target molecule synthesis
• Operate Schlenk lines, gloveboxes, and other inert-atmosphere systems for sensitive compounds
• Use PAT tools (UPLC, LCMS, NMR, IR, Fluroescence, DLS) to monitor reactions, ensure quality control, and generate high-quality data for ML workflows
• Leverage automation and AI-driven platforms to accelerate workflows and reduce experimental cycle times
• Collaborate with engineers, ML scientists, and stakeholders to validate model-suggested conditions, analyze trends, troubleshoot issues, and communicate results clearly through reports, discussions, and presentations
• Document results, maintain accurate digital records and adhere to EHS and laboratory best practices

What You’ll Need to Succeed

• M.S. in Chemistry or related discipline (organic, organometallics, catalysis) with 2+ years of hands-on high-fidelity laboratory experience in an academic or industry setting, or B.S. + 5 years
• Hands-on experience in organic/inorganic synthesis, purification, chromatographic techniques, product analysis
• Strong understanding of retrosynthesis, reaction mechanisms, and method optimization workflows
• Proficiency with analytical techniques such as TLC, HPLC, LCMS, NMR, and IR
• Ability to follow SOPs and work safely with diverse chemical reagents and automated platforms
• Ability to thrive in a fast-paced, multidisciplinary research environment
• Required proficiency in using SciFinder, Reaxys, Chemdraw to search public database and literature
• Basic proficiency in Python or other scripting languages for data handling
• Good document practices, strong attention to detail and a proactive, problem-solving mindset
• Effective oral and written communication skills; contributed to internal reports, technical documentation, or peer-reviewed publications

Bonus Points For

• Experience with high-throughput or AI-driven automated platforms
• Authored publications in peer-reviewed journals in chemical catalysis, organic methodology
• Ability to handle air/moisture/light sensitive compounds

Your Impact at LILA

As a Principal Security Engineer focused on AI Security, you will define and drive the technical strategy for securing how AI is used across Lila's enterprise. You will operate as a senior individual contributor, partnering with IT and business teams to ensure safe and compliant adoption of AI tools and platforms.

While Lila builds AI-powered systems, this role is primarily focused on securing the use of third-party and internally deployed AI tools across the enterprise — ensuring sensitive data, intellectual property, and scientific workflows are protected as AI becomes deeply embedded in how work gets done.

What You'll Be Building

• Enterprise AI Security Strategy — Define and implement security controls and guardrails for the use of AI tools (e.g., LLM APIs, SaaS AI platforms, and internal AI services) across the organization.
• AI Gateway & Agentic Gateway Security — Design and implement AI gateway controls to manage and monitor access to external and internal AI systems. Secure agentic workflows by enforcing identity, authorization, tool-use constraints, and policy controls for autonomous or semi-autonomous agents.
• AI Red Teaming & Adversarial Testing — Conduct red teaming and adversarial testing focused on enterprise AI usage, including prompt injection, data exfiltration, jailbreaks, and abuse of connected tools and plugins.
• Data Protection for AI Usage — Develop and enforce controls to prevent sensitive data leakage through AI systems, including input/output filtering, data classification, tokenization, and secure handling of prompts, embeddings, and outputs.
• Multi-Layer AI Security (Network, Endpoint, Data) — Integrate AI security into existing enterprise security layers: network visibility and control over AI service access, API traffic inspection, and zero trust enforcement; endpoint security for developer machines, research environments, browsers, and plugins; data layer controls ensuring proper handling of sensitive data when interacting with AI systems.
• AI Threat Modeling (Enterprise Context) — Develop threat models focused on enterprise AI usage, including risks such as data leakage, prompt injection, model misuse, supply chain risks from AI vendors, and unauthorized agent actions.
• Vendor & Platform Security — Assess and guide secure adoption of third-party AI vendors and platforms, including evaluating data handling practices, model behavior, and integration risks.
• Incident Response for AI Usage — Define and support response approaches for AI-related incidents, such as sensitive data exposure, policy violations, or misuse of AI tools.
• Cross-Functional Technical Leadership — Partner with Legal, Compliance, IT, and Engineering to align AI usage with regulatory requirements, data governance policies, and responsible AI practices.
• Security Enablement — Contribute to internal guidance and education on safe AI usage, including secure prompting, data handling, and appropriate use of AI tools.
• Security Tooling & Implementation — Evaluate and implement tooling for AI security, including AI gateways, DLP integrations, monitoring solutions, and policy enforcement mechanisms.

What You’ll Need to Succeed

• 8+ years of experience in information security, with strong expertise in enterprise, cloud, or application security.
• Hands-on experience designing and implementing security controls in enterprise environments.
• Familiarity with AI/ML systems and how modern AI tools (LLMs, copilots, APIs) are used in practice.
• Experience with cloud platforms (AWS/GCP), SaaS security, and zero trust architectures.
• Experience with data protection technologies (e.g., DLP, data classification, access controls).
• Practical experience with threat modeling, red teaming, or adversarial testing.
• Strong communication and influence skills across technical and non-technical stakeholders.

Bonus Points For

• Experience securing enterprise use of LLMs, copilots, or generative AI platforms.
• Familiarity with AI gateways, prompt filtering, or model interaction controls.
• Experience evaluating or securing third-party AI vendors and APIs.
• Background in regulated environments (biotech, healthcare, defense, or government).
• Experience with browser security, endpoint controls, or SaaS security platforms.
• Knowledge of privacy-enhancing technologies or confidential computing.
• Contributions to AI/ML security research or community.

Your Impact at LILA

We are seeking a Scientist (II) to join our Physical Sciences team. This role will focus on assisting in the design and development of a high throughput chemical synthesis platform, with emphasis on medicinal chemistry and drug delivery applications. The ideal candidate will have experience synthesizing, analyzing, and optimizing novel molecules to build out structure-activity relationships for a library of compounds. This position will work closely with others across the chemistry, formulations, engineering, machine learning, and data science teams to help establish next-generation tools for therapeutic development and drug delivery. Your work will bridge the physical sciences and bioanalytical domains, enabling high-throughput experimentation for closed-loop optimization of organic compounds.

What You'll Be Building

• Design, synthesize, and optimize novel lipids, small molecules, and other combinatorial chemistry compound libraries for drug delivery applications
• Design and deploy high-throughput synthesis strategies, build automated assay platforms, and develop innovative approaches to interrogate large chemical spaces
• Partner closely with chemistry, computational, and automation teams to establish structure-activity relationships for compound libraries to guide iterative design strategies
• Implement data-driven approaches to analyze screening outputs and guide iterative molecule design.
• Work with and manage projects with CDMOs for research-grade synthesis, with considerations towards scale-up of lead compounds
• Establish best practices for screening data quality, reproducibility, and assay robustness.
• Collaborate across disciplines to translate screening hits into validated chemical starting points for therapeutic programs.

What You’ll Need to Succeed

• Ph.D. in Chemistry, Chemical Engineering, or a related field.
• ≥ 1 years of experience with automation, instrumentation, and integrating real-time analytics into experimental workflows.
• Strong background in organic synthesis, with experience designing and synthesizing novel organic compounds.
• Excellent problem-solving, communication, and collaboration skills.

Bonus Points For

• Familiarity with novel lipid design for drug delivery applications
• Prior knowledge and implementation of biodegradability and tolerability design principles, with working knowledge of biological implications of compound moieties
• Prior experience working in an autonomous or self-driving chemical lab environment driving organic chemistry transformations
• Hands-on experience with AI-driven experimental design or Bayesian optimization
• Background in scaling workflows from proof-of-concept to routine, high-throughput operation

Your Impact at LILA

As a Scientist on our Physical Sciences team, you will contribute to the development of cutting-edge flow chemistry workflows. You’ll help design, build, and optimize flow chemistry platforms that integrate real-time analytics, advanced control strategies, and AI-driven decision-making. In this role, you’ll work closely with systems engineers and AI scientists to help expand autonomous chemistry capabilities and accelerate discovery at scale. 

What You'll Be Building

• Design & Commission: Architect and develop versatile flow chemistry platforms for autonomous synthesis, ensuring seamless integration with the Lila platform.
• Integrate & Scale: Build, control, and optimize flow reactors and inline analytics. Interface flow chemistry platforms with robotic and sensing systems. 
• Workflow Optimization: Tune flow chemistry platform design and software pipelines for high-throughput closed-loop experimentation with rich metadata capture. 
• Closed-Loop Execution: Collaborate with AI teams to run iterative experiments in real time, enabling fast optimization and discovery cycles.
• Collaboration & Documentation: Work with chemists, material scientists, engineers, and data scientists to document systems, share insights, and refine best practices in autonomous flow chemistry.

What You’ll Need to Succeed

• Ph.D. or M.S. in Chemical Engineering, Chemistry, or a related field. 
• ≥ 1 years (for PhD, 4+ years for M.S ) of hands-on experience in flow chemistry, microfluidics, or microreaction engineering. 
• ≥ 1 years of experience with automation, instrumentation, and integrating real-time analytics into experimental workflows. 
• Strong background in homogeneous chemical catalysis and organic synthesis. 
• Proficiency in Python for scripting, data analysis, and instrument control. 
• Excellent problem-solving, communication, and collaboration skills. 

Bonus Points For 

• Prior experience working in an autonomous or self-driving lab chemical lab environment driving organic chemistry transformations. 
• Familiarity with cloud-based instrumentation control and orchestration.
• Hands-on experience with AI-driven experimental design or Bayesian optimization.
• Background in scaling workflows from proof-of-concept to routine, high-throughput operation.
• Contributions to open-source lab automation or scientific software projects.

Your Impact at LILA

Lila Sciences is seeking an Industrial Engineer to own and architect the physical layout of our AI Science Factories. In this role, you will be responsible for integrating lab instrumentation and robotics into a cohesive, efficient factory design. You will collaborate closely with hardware engineering, science teams, robotics, facilities, and operations to create layouts that are safe, scalable, and engineered for high-throughput autonomous research. This role is central to translating complex cross-functional requirements into a factory environment that enables Lila’s next-generation scientific capabilities. 

What You'll Be Building

• Own the end-to-end factory layout, including spatial planning, adjacency mapping, and utility requirements
• Integrate lab instrumentation layouts from diverse scientific and engineering domains into a unified, high-performance factory design.
• Collaborate with hardware, robotics, science, automation, safety, and facilities teams to incorporate requirements for utilities, safety, accessibility, maintenance, and environmental controls.
• Build and maintain accurate 2D and 3D CAD models of the full factory layout; drive version control and change management for layout updates.
• Work with robotic teams to run simulations and scenario analyses to assess throughput, operational efficiency, and bottlenecks.
• Partner with construction, facilities, and external vendors to ensure physical buildouts reflect the intended design and can scale with future demand.
• Develop standards, documentation, and layout guidelines for new lab instrumentation and factory expansions.

What You’ll Need to Succeed

• BS/MS degree in Industrial Engineering, Mechanical Engineering, Manufacturing Engineering, Systems Engineering, or related field.
• Experience designing factory, lab, or production layouts in high-complexity environments.
• Proficiency with CAD tools (e.g., AutoCAD, REVIT, SolidWorks).
• Strong understanding of workflow optimization, material flow, ergonomics, and spatial systems.
• Ability to collaborate across multidisciplinary engineering and scientific teams.
• Clear communication and documentation skills.

Bonus Points For

• Experience with robotic or automated systems and their physical integration into facilities.
• Familiarity with lab/industrial utility requirements (HVAC, gases, power, chemicals, drainage).
• Experience in R&D facilities, pilot plants, or advanced automation environments.