About Graphcore

At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Job Summary

As a researcher at Graphcore, you will contribute to the advancement of AI research, investigating new ideas that push the limits on important AI/ML problems. Specialised hardware has been the key driver of the progress of AI over the last decade, and we believe that hardware-aware AI algorithms and AI-aware hardware developments will continue to be critical to advancing this exciting field. As such, we’re looking for candidates who are keen scientists and engineers, with the theoretical and practical skills needed for impactful AI research.

We are looking for researchers with experience of AI in low-power, edge and embodied scenarios such as robotics, autonomous driving and augmented/virtual reality. We are interested in the training and deployment of multimodal AI models in these contexts, covering areas such as world models, real-time computer vision, generating and reasoning over audio/video streams.

The Team

Graphcore Research participates in both fundamental and applied research, to characterise the computational requirements of machine intelligence and to demonstrate how hardware can drive the next generation of innovative AI models. We publish at leading AI/ML conferences (NeurIPS, ICML, ICLR) as well as specialist workshops, and collaborate with other research teams and organisations across the world.

We pride ourselves on being a supportive and collaborative team, where we organise around our individual research interests to solve problems together in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications, including for sequence- and graph-based data. We’re based across London, Cambridge and Bristol, with projects and discussions that involve all our locations.

Perhaps the best way to get an idea of what we’re all about is to read one of our papers or an article on our blog. If you’re excited to work at the cutting edge of AI supported by new hardware and want to develop your skills in this area, we’d love to hear from you!

Responsibilities and Duties

• Generate AI/ML ideas, design experiments, implement them & evaluate results.
• Prepare, submit & present your work to AI conferences and workshops.
• Collaborate with researchers, silicon and software engineers at Graphcore to help define, build and test Graphcore’s next generation of AI hardware.

About you:

Essential:

• Master’s, PhD or equivalent experience in a technical discipline (e.g., Maths, Statistics, Computer Science, Physics, Chemistry, Biomedical Engineering).
• Experience in embodied AI, world models or robotics.
• Python programming in a modern deep learning framework, e.g. PyTorch or JAX.
• Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling.
• Capable of designing, executing and reporting from ML experiments.
• Mathematics skills to support the above: calculus, probability theory and linear algebra.
• Experience submitting papers to international scientific conferences or workshops.

Desirable:

• Lower-level programming for hardware efficiency, e.g. C++/CUDA/Triton.
• Practical familiarity with hardware capabilities for deep learning – threads, caches, vector & matrix engines, data dependencies, bus widths and throttling.
• Practical familiarity with software stacks for deep learning – compilation, kernel fusion, XLA/ATen ops, streams, and asynchronous execution.
• Conference or workshop submissions in the fields of embodied AI, world models, or robotics.

Benefits

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications

Job Summary

As an Aerospace Algorithms Engineer at MORSE you will be working on a broad set of applications developing novel physics, statistical, and mathematical models for use in mission planning tools used by military personnel and first responders. MORSE is looking for engineers with a strong background in physics, aerospace, robotics, math, and statistics who are also able to develop their algorithms in software to function efficiently and be readily testable.

Responsibilities:

• Develop and own algorithms throughout their lifecycle, including conception, development, documentation, deployment, and testing.

• Process and analyze raw data

• Simulate and validate algorithmic performance using dynamic systems.

• Present technical work through white papers, analysis test reports, and oral presentations.

• Collaborate with cross-functional teams to ensure seamless integration of algorithms into software solutions.

Skills and Requirements

The candidate must have the ambition to own mission planning algorithms for their entire lifecycle: conception of the solution, development, documentation, deployment in software, and testing. Most importantly, the candidate must be passionate about developing solutions that are fieldable!

• US CITIZENSHIP REQUIRED or the ability to obtain a U.S. Security Clearance.

• MS or PhD in Aerospace Engineering, Robotics, Physics or other relevant field.

• Proficiency in Python algorithm and software development practices.

• Strong background in physics, math, and statistics.

• Experience with developing algorithms and simulations.

• Experience simulating dynamic systems to test and validate algorithmic performance

• Experience describing systems via equations of motion derived from first-principle engineering analysis

• Experience presenting technical work through white papers, analysis test reports, and oral presentations.

• 5+ years of experience

Job Summary

As an Aerospace Algorithms Engineer at MORSE you will be working on a broad set of applications developing novel physics, statistical, and mathematical models for use in mission planning tools used by military personnel and first responders. MORSE is looking for engineers with a strong background in physics, aerospace, robotics, math, and statistics who are also able to develop their algorithms in software to function efficiently and be readily testable.

Responsibilities:

• Develop and own algorithms throughout their lifecycle, including conception, development, documentation, deployment, and testing.

• Process and analyze raw data

• Simulate and validate algorithmic performance using dynamic systems.

• Present technical work through white papers, analysis test reports, and oral presentations.

• Collaborate with cross-functional teams to ensure seamless integration of algorithms into software solutions.

Skills and Requirements

The candidate must have the ambition to own mission planning algorithms for their entire lifecycle: conception of the solution, development, documentation, deployment in software, and testing. Most importantly, the candidate must be passionate about developing solutions that are fieldable!

• US CITIZENSHIP REQUIRED or the ability to obtain a U.S. Security Clearance.

• MS or PhD in Aerospace Engineering, Robotics, Physics or other relevant field.

• Proficiency in Python algorithm and software development practices.

• Strong background in physics, math, and statistics.

• Experience with developing algorithms and simulations.

• Experience simulating dynamic systems to test and validate algorithmic performance

• Experience describing systems via equations of motion derived from first-principle engineering analysis

• Experience presenting technical work through white papers, analysis test reports, and oral presentations.

• 5+ years of experience

MORSE is seeking a talented Robotics Software Engineer to join our team. The ideal candidate will have a strong background in embedded systems, navigation algorithms, and autonomy. You will be responsible for architecting systems, implementing custom algorithms, and integrating novel control systems into our aerial vehicles. This role will involve developing and debugging software, configuring systems for flight tests, and supporting the end-to-end development of prototype vehicles. A passion for innovation and the ability to bring novel Unmanned Aerial Systems (UAS) from concept to flight is essential.

Responsibilities:

• Architect systems with multiple microcontrollers, defining component roles and managing requirements.

• Implement custom navigation algorithms and autonomy logic in Rust and C++.

• Analyze vehicle flight logs and debug GNC and autonomy issues

• Develop and write LIDAR sensor drivers in C++ and Rust.

• Handle system configuration, ground station setup, and data management during local and remote flight tests.

• Develop control and path planning algorithms for aerial vehicles and integrate them into the PX4 ROS communications layer.

• Implement drivers for novel control actuation and integrate them into PX4 or other flight controllers.

• Incorporate flight models into the existing Python flight simulator and use the simulator for algorithm development.

• Develop Software-In-the-Loop (SWIL) and Hardware-In-the-Loop (HWIL) testing capabilities.

• Aid in system architecture, selection, and integration of flight controllers, electronics, and sensors.

• Support the development, integration, and testing of prototype vehicles.

• Write, test, and debug drivers such as CANopen actuators and beyond line-of-sight radios in C++ and Python.

• Demonstrate familiarity with low-level embedded programming concepts such as memory management, data structures, algorithms, and bit manipulation.

Requirements:

• U.S. Citizenship required and ability to obtain a U.S. Security Clearance

• Bachelor’s degree in Robotics, Electrical Engineering, Computer Engineering, Computer Science, Aerospace Engineering or a related field. Master’s degree preferred.

• Strong skills in C++, Rust, and Python.

• Experience in navigation algorithms (SLAM, path planning) and autonomy logic.

• Experience with low-level embedded programming and microcontrollers.

• Experience with PX4 or other flight controllers

• Skilled in system architecture, component definition, and integration of prototype vehicles.

• A passion for taking novel UAS from concept to flight!

Your Impact at LILA

Lila is seeking a motivated SCADA Engineer to contribute to the design, development, and implementation of control systems for automated scientific equipment. This role involves applying core engineering principles to support PLC controls, robotics integration, troubleshooting systems, and collaborating within cross-functional teams to enhance laboratory automation.

What You'll Be Building

• Assist in designing, programming, and deploying control systems using PLC and SCADA technologies to optimize laboratory workflows.
• Support the integration and testing of advanced robotics and conveyance systems within existing automation frameworks.
• Assist in integrating 3rd party equipment and vendor software into SCADA and make custom HMIs to aid in user controls.
• Contribute to the design and implementation of safety systems to safely operate a mix of lab equipment and robotics.
• Collaborate with software teams to support the integration of control systems with broader IT/OT factory infrastructure.
• Create, update, and maintain engineering documentation, including P&ID diagrams, wiring schematics, control narratives, and instrument IO lists.
• Support multi-team automation projects by independently executing technical tasks, meeting milestones, and adhering to engineering best practices.
• Perform calibration, testing, troubleshooting, and validation of control systems to ensure they meet performance, accuracy, and safety standards.
• Work closely with subject matter experts (SMEs) and project teams to understand technical requirements and solve moderately complex hardware/software challenges.
• Identify recurring technical issues and implement improvements to enhance system reliability and operational efficiency.

What You’ll Need to Succeed

• 2–4 years of experience in designing, implementing, or maintaining control systems, preferably in automated manufacturing or laboratory environments.
• Solid understanding of PLCs, HMI, SCADA, and related automation software and hardware.
• Familiarity with industrial networking basics in OT deployments (e.g., IP addressing, basic routing).
• Experience reading and creating detailed engineering documents and schematics using tools like AutoCAD, SolidWorks Electrical, or similar.
• Hands-on experience or academic background in robotics integration and programming.
• Effective communication and collaborative skills for working within project teams and with internal stakeholders.
• Strong analytical and problem-solving skills, with the ability to independently execute solutions for well-defined technical issues.

Bonus Points For

• Ignition SCADA Core training and HMI design experience.
• Structured text programming experience in TwinCAT, Python, C++, etc.
• Familiarity with communication protocols like OPC-UA, MQTT, and REST APIs.
• Exposure to safety system design concepts and classifications like SIL or PL.
• Basic understanding of managed network switches, port addressing/IP subnetting, and DHCP services.
• Ability to troubleshoot basic traffic flows between OT networks and cloud instances.

Your Impact at LILA

We're building autonomous robotic systems that serve as the intelligent physical infrastructure of our Scientific Superintelligence Platform at Lila. To support our robotics research roadmap, we need to scale robot data collection to produce high-quality robot data, collected by humans, at scale, day after day while improving per-operator throughput, lowering churn, and keeping data quality consistent across every supervisor and shift

We're hiring an Operations Manager to own that scale-up end-to-end.

As Data Operations Manager, you'll own the day-to-day function that generates the training data powering Lila's robotic systems. That means managing the supervisors who run our data collection shifts, setting the conditions for consistent operator performance, and making sure every hour of work on the floor translates into high-quality, usable data for our research team.

This is a builder role. The team is early — a growing group of operators across two shifts — and the processes, metrics, and programs that will scale it are still being shaped. You'll design and own them. You'll report directly to the Robotics team and serve as the primary operational link between the floor and Robotics Research.

What You'll Be Building

• Run the operation: Own the day-to-day operation across all shifts. Set throughput targets, monitor adherence, debug when shifts under-deliver, and make weekly calls on staffing, scheduling, and task allocation
• Manage the team: You'll manage the supervisors who directly run our operators. Set clear goals, run a consistent performance loop, and grow the supervisory bench as shifts, and sites, expand
• Drive retention and engagement: Data collection is physical, repetitive, attention-heavy work. Design and continuously refine onboarding, training, performance incentives, recognition, and scheduling so operators stay engaged and the bar keeps rising. Approach this with a product mindset: hypothesize, ship, measure, iterate
• Own throughput and quality metrics. Set targets, build the dashboards, and run the review cadence that make performance visible across the team. Reduce reject rates, compress reset time, and increase usable hours per shift
• Plan capacity: Translate research priorities into concrete operational plans — operator allocation, supervisor coverage, equipment requirements, and risk. Forecast throughput, flag potential misses early, and re-plan as priorities evolve
• Scale the footprint: Partner with facilities, recruiting, and leadership to expand the operation across additional shifts and, in time, additional sites. Maintain an operational playbook that makes opening each new shift or site repeatable rather than bespoke
• Be the bridge to research: Meet with the research team to understand upcoming priorities: which tasks, which embodiments, what success looks like. Translate those needs into shift plans, and surface friction (poor reset ergonomics, ambiguous instructions, unreliable hardware) before it costs the team hours

What You’ll Need to Succeed

• 4+ years of operations or program management experience, including direct people management
• A track record of running shift-based, throughput-driven operations — ****warehousing, manufacturing, contact centers, data labeling, clinical ops, field operations or comparable
• Demonstrated success reducing churn or improving retention in a frontline workforce: We want to hear the specifics: the baseline, the intervention, and the outcome
• Comfort with metrics: You should be able to look at our shift summary, immediately spot what's interesting, and know what to ask for next
• Builder mindset: This is a function being built, not inherited. Some processes are still taking shape, and we are looking for the right person who sees that as an opportunity to grow and deliver
• Strong written communication — ****you will be the connection between the floor and research and engineering teams, and much of that work happens in documentation
• Willingness to be on-site and on-floor: This role depends on presence and proximity to the team

Bonus Points For

• Experience managing managers or building a supervisor layer from scratch
• Background in robotics, autonomous systems, or physical AI data collection
• Experience scaling a frontline team from under 20 to 100+
• Familiarity with workforce management software, shift-scheduling tooling, or QA workflow tools
• Background in industrial engineering, operations research, or a related quantitative field

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

Join us in shaping the future of science! We are seeking Sr Principal, and Principal Software Engineers with full stack experience to join our software org, where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. Our teams span across App, Data, SSR, and LaS 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!

Our Software Teams

The Application Team (App)- They build the operating system for AI-driven science. Their platform unifies Machine Learning, Life Sciences, Physical Sciences, and Software into one AI-native experience — where a scientist can go from hypothesis to experiment to result in a single conversation. They ship the agents, the integrations, and the interfaces that make that possible.

The Scientific System of Record Team (SSR) - They build the memory layer for Lila's operations. It answers two questions:what did we plan to build? and what actually happened? These systems connect scientific intent to physical reality. Together with the data and automation teams, their systems ensure reproducibility and close the Design-Build-Test-Learn (DBTL) loop.

The Lab as Software Team (LaS)- They act as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab.

The Data Platform Team (Data)- They build and support the data systems that underpins Lila's AI Science Factory™. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence™, so the science moves faster and each experiment makes the next one smarter.

What You'll Be Building

• Design & Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.
• Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
• Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.
• Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
• Cloud & Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.
• Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.

What You'll Need To Succeed  

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 8-15 years of engineering experience building and deploying large-scale systems in production. You must be strong in either front-end or backend.
• Full Stack Development: Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)
• Hands on experience using AI coding assistants to drive productivity is required.
• Communication & Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.
• Problem Solving: Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.

Bonus Points For

• Cloud & DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
• Experience with ORMs: Experience with and web services for CRUD services (SQLModel, FastAPI, Django).
• Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).
• Familiarity with Python for Science: Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).
• Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.
• Experience with laboratory devices, robotics, or hardware drivers.

Your Impact at LILA

Join us in shaping the future of science! We are seeking Staff, Senior II, and Senior I Software Engineers with either frontend or backend experience to join our software org, where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. Our teams span across App, Data, SSR, and LaS 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!

Our Software Teams

The Application Team (App)- They build the operating system for AI-driven science. Their platform unifies Machine Learning, Life Sciences, Physical Sciences, and Software into one AI-native experience — where a scientist can go from hypothesis to experiment to result in a single conversation. They ship the agents, the integrations, and the interfaces that make that possible.

The Scientific System of Record Team (SSR) - They build the memory layer for Lila's operations. It answers two questions:what did we plan to build? and what actually happened? These systems connect scientific intent to physical reality. Together with the data and automation teams, their systems ensure reproducibility and close the Design-Build-Test-Learn (DBTL) loop.

The Lab as Software Team (LaS)- They act as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab.

The Data Platform Team (Data)- They build and support the data systems that underpins Lila's AI Science Factory™. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence™, so the science moves faster and each experiment makes the next one smarter.

What You'll Be Building

• Design & Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.
• Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
• Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.
• Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
• Cloud & Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.
• Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.

What You’ll Need to Succeed

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 5-10 years of engineering experience building and deploying large-scale systems in production. You must be strong in either front-end or backend.
• Full Stack Development: Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)
• Hands on experience using AI coding assistants to drive productivity is required.
• Communication & Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.
• Problem Solving: Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.

Bonus Points For

• Cloud & DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
• Experience with ORMs: Experience with and web services for CRUD services (SQLModel, FastAPI, Django).
• Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).
• Familiarity with Python for Science: Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).
• Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.
• Experience with laboratory devices, robotics, or hardware drivers.

Your Impact at LILA

The Scientist I/II, Organic Chemistry will develop, execute, and optimize modern chemical transformations that support Discovery Chemistry efforts across Lila’s platform, with a focus on the rapid synthesis of small molecules and structurally diverse chemical matter. This role is intended for an experimental organic chemist who combines strong foundations in synthetic chemistry with hands-on experience in high-throughput experimentation (HTE), reaction workup, and analytical characterization.

Working closely with Discovery Chemistry, analytical chemistry, automation, screening, and AI/computational teams, this scientist will help build and apply efficient chemistry workflows that accelerate molecular design–make–test–analyze cycles. The Scientist II will contribute to reaction development, analog generation, and route execution using modern organic chemistry approaches that are compatible with scalable, data-rich, and increasingly automated discovery environments.

This role is ideal for a chemist excited by solving synthetic problems at the interface of reaction innovation, high-throughput experimentation, process efficiency, and analytical insight, and who is motivated to help shape next-generation discovery workflows beyond traditional bench chemistry.

What You'll Be Building

• Design, execute, and optimize chemical transformations relevant to Discovery Chemistry programs, with emphasis on the rapid synthesis of small molecules and analog series.
• Apply modern synthetic organic chemistry to enable efficient exploration of structurally diverse and medicinally relevant chemical space.
• Plan and perform multi-step synthesis, reaction optimization, workup, purification, and compound characterization in support of molecular discovery campaigns.
• Design and execute HTE workflows for reaction screening, condition optimization, reagent evaluation, and rapid assessment of transformation scope.
• Develop robust approaches for reaction setup, reaction workup, sample preparation, and analytical readout to support fast and information-rich experimentation.
• Use analytical tools such as chromatography, NMR, and related methods to assess reaction performance, characterize products, and guide synthetic decisions.
• Contribute to the development of practical and scalable chemistry workflows that integrate reaction discovery, reaction optimization, and downstream compound generation.
• Partner closely with Discovery Chemistry scientists to translate molecular design concepts into executable synthetic strategies and experimentally tractable reaction plans.
• Collaborate with analytical chemistry and automation teams to build workflows that connect reaction execution with streamlined workup, purification, and data generation.
• Support the adaptation of synthetic workflows to parallel, automated, or robotics-enabled platforms where appropriate.
• Interpret reaction and analytical data rigorously, identify bottlenecks, and propose solutions to improve efficiency, robustness, and reproducibility.

What You’ll Need to Succeed

• PhD in Organic Chemistry, Medicinal Chemistry, or a closely related discipline with relevant postdoctoral and/or industry experience.
• Strong expertise in synthetic organic chemistry, including design and execution of multi-step synthesis and development of chemical transformations relevant to small molecule discovery.
• Hands-on experience with HTE for reaction screening, optimization, or scope evaluation.
• Experience with reaction workup, sample preparation, purification, and analytical characterization in fast-paced synthetic workflows.
• Strong working knowledge of analytical methods commonly used to support organic synthesis.
• Demonstrated ability to troubleshoot challenging reactions and independently solve synthetic and experimental problems.
• Strong understanding of how reaction design, execution, workup, and analysis fit together in efficient discovery workflows.
• Ability to work effectively in interdisciplinary environments spanning chemistry, analytics, automation, and computational sciences.
• Strong organizational, documentation, and communication skills, with commitment to scientific rigor and reproducibility.

Bonus Points For

• Experience supporting Discovery Chemistry or medicinal chemistry programs in biotech, pharma, or advanced research environments.
• Familiarity with modern reaction classes relevant to small molecule discovery, including coupling chemistry, heterocycle synthesis, late-stage functionalization, and rapid analog generation.
• Experience with parallel synthesis or robotics-enabled chemistry workflows.
• Exposure to data-rich, AI-enabled, or platform-based R&D environments.
• Collaborative mindset and enthusiasm for building modern chemistry capabilities that go beyond traditional bench-scale synthesis.

Your Impact at LILA

The Scientist I/II, Process Chemistry will develop and apply modern process chemistry approaches to support Discovery Chemistry efforts across Lila’s platform, with a focus on reaction/reactor engineering, process design, high-throughput experimentation, and digitalized chemistry workflows for small molecules and related molecular matter. This role is intended for a hands-on scientist who combines strong foundations in synthetic and process chemistry with an engineering mindset and experience building practical, scalable, and data-rich experimental workflows.

Working closely with Discovery Chemistry, analytical chemistry, automation, platform engineering, and AI/computational teams, this scientist will design, execute, and optimize reaction and process workflows that improve the speed, robustness, and scalability of chemical transformations. The Scientist I/II will help bridge early discovery chemistry and modern process development by establishing experimentally efficient, digitally enabled, and automation-compatible approaches to reaction screening, process optimization, and chemistry execution.

This role is ideal for a scientist excited by the intersection of chemistry, engineering, high-throughput platforms, process intensification, and digital experimentation, and who wants to help shape next-generation process chemistry capabilities beyond traditional bench development.

What You'll Be Building

• Design, execute, and optimize process-relevant chemical transformations that support Discovery Chemistry programs and the generation of small molecules.
• Develop reaction and process workflows with emphasis on engineering rigor, scalability, reproducibility, throughput, and data quality.
• Apply high-throughput experimentation (HTE) to reaction screening, process optimization, condition scouting, and evaluation of process-relevant variables.
• Build and execute workflows that connect reaction setup, process screening, workup, analytical readout, and data capture into efficient experimental cycles.
• Contribute to the design of digitally enabled process chemistry workflows, including structured experimental data generation, electronic documentation, and integration of chemistry data into computational and AI-ready systems.
• Collaborate with automation and platform teams to develop and adapt reaction and process workflows for robotics-enabled experimentation.
• Work closely with analytical chemistry teams to ensure rapid and informative analytical support for reaction monitoring, impurity assessment, and process decision-making.
• Evaluate reaction performance through both chemistry and engineering lenses, including yield, selectivity, impurity formation, mass balance, robustness, throughput, and operational simplicity.
• Establish best practices for AI-enhanced process design in early discovery settings, balancing speed and molecular access with process understanding and future scalability.
• Stay current with advances in modern process chemistry, reaction engineering, HTE, digitalization, automation, and enabling technologies relevant to next-generation discovery chemistry.

What You’ll Need to Succeed

• PhD in Process Chemistry, Organic Chemistry, Chemical Engineering, Medicinal Chemistry, or a related discipline with relevant postdoctoral and/or industry experience.
• Strong hands-on experience in process chemistry, reaction development, or scale-relevant synthetic chemistry.
• Demonstrated experience applying engineering principles to chemical process design, optimization, and troubleshooting.
• Experience with HTE for reaction or process screening, optimization, and data-rich experimentation.
• Strong understanding of key process variables in discovery chemistry.
• Experience with reaction workup, sample handling, purification, and analytical interpretation in fast-paced chemistry environments.
• Hands-on familiarity with analytical tools commonly used to support process chemistry.
• Experience generating well-structured experimental data to support reproducibility and digital workflows.
• Ability to troubleshoot complex experimental problems and independently drive practical, technically sound solutions.
• Strong collaborative skills and ability to work effectively across chemistry, analytics, automation, engineering, and computational teams.

Bonus Points For

• Experience supporting Discovery Chemistry or small molecule R&D in biotech, pharma, or advanced platform environments.
• Familiarity with modern process chemistry in early discovery settings, including rapid route improvement, robustness assessment, impurity understanding, and scalable reaction design.
• Experience with miniaturized process screening, parallel reactors, or robotics-enabled chemistry platforms.
• Experience contributing to the digitalization of process chemistry, including structured data capture, ELNs, workflow automation, or AI/ML-enabled experimental environments.
• Ability to connect chemistry execution with broader platform goals such as throughput, automation compatibility, and data generation.
• Strong scientific curiosity and enthusiasm for building next-generation process chemistry capabilities that go beyond traditional development paradigms.

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

The Senior Scientist, Analytical Chemistry will develop and deploy advanced analytical and characterization strategies to support Discovery Chemistry efforts across Lila’s platform, with a focus on enabling the rapid design, synthesis, screening, and optimization of small molecules and related molecular matter. This scientist will play a key role in generating high-quality, information-rich experimental data that informs chemistry decisions and accelerates platform learning.

Working closely with Discovery Chemistry, automation, AI/computational, and screening teams, this role will establish and scale multimodal characterization workflows that go beyond traditional analytical chemistry approaches. The Senior Scientist will help build an integrated analytical capability spanning compound characterization, reaction monitoring, molecular profiling, and high-throughput data generation to support fast and iterative design–make–test–analyze cycles.

This role will be critical to shaping Lila’s next-generation discovery engine by combining deep expertise in analytical chemistry with high-throughput experimentation, multimodal data generation, AI-enabled workflows.

What You'll Be Building

• Develop, optimize, and implement analytical and multimodal characterization workflows to support Discovery Chemistry programs and molecular discovery campaigns.
• Support the design, synthesis, screening, and optimization of small molecules by delivering rapid, reliable, and information-rich analytical data.
• Lead analytical method development for compound identification, purity assessment, impurity profiling, reaction monitoring, and molecular characterization using techniques such as liquid chromatography, mass spectroscopy, NMR, and complementary orthogonal methods.
• Build characterization strategies that extend beyond traditional analytical methods, incorporating multimodal measurements that provide deeper insight into molecular identity, reaction outcomes, physicochemical properties, and structure–function relationships.
• Partner closely with Discovery Chemistry and screening teams to support high-throughput screening and high-throughput experimentation workflows, including rapid sample analysis, reaction triage, and compound profiling.
• Collaborate with automation and platform teams to integrate analytical instrumentation and data pipelines into robotics-enabled and scalable discovery workflows.
• Work closely with AI and computational teams to ensure analytical datasets are structured, interoperable, and useful for model development, closed-loop learning, and iterative molecule design.
• Establish robust workflows for reaction monitoring, in-process analytics, final compound quality assessment, and characterization of complex mixtures or intermediates.
• Troubleshoot analytical and characterization challenges related to sample preparation, instrumentation, method robustness, data interpretation, and workflow integration.
• Contribute to the development of platform-level capabilities for data-rich molecular discovery, including scalable characterization pipelines, method standardization, and best practices for analytical rigor.

What You’ll Need to Succeed

• PhD in Analytical Chemistry, Organic Chemistry, Pharmaceutical Sciences, Chemical Biology, or a related scientific discipline with 5–8+ years of relevant industry or high-performance research experience.
• Deep expertise in analytical chemistry and molecular characterization in support of chemistry-driven discovery efforts.
• Strong hands-on experience with key analytical techniques for small molecule analysis.
• Demonstrated experience developing analytical methods for compound characterization, reaction monitoring, impurity analysis, and purity assessment.
• Experience supporting Discovery Chemistry, medicinal chemistry, synthetic chemistry, or other molecule-focused R&D environments.
• Strong understanding of how analytical data informs compound progression, screening decisions, reaction optimization, and molecular design.
• Experience working with or supporting high-throughput workflows, including rapid analytical turnaround in fast-paced research settings.
• Ability to solve complex analytical problems independently and work effectively across interdisciplinary teams spanning chemistry, screening, automation, and computational sciences.
• Strong documentation, communication, and data interpretation skills, with a commitment to rigor, reproducibility, and scientific quality.

Bonus Points For

• Experience with multimodal characterization approaches that combine orthogonal measurements to generate deeper insight into molecular systems and discovery workflows.
• Experience supporting high-throughput screening, reaction screening, or automated discovery platforms.
• Familiarity with analytical workflows integrated with robotics, liquid handlers, autosamplers, or other automation-enabled laboratory systems.
• Experience working in AI-enabled or highly data-driven R&D environments where experimental data is used to drive predictive modeling or closed-loop optimization.
• Knowledge of characterization approaches that extend beyond traditional compound QC, including molecular profiling, reaction analytics, and property-focused measurements.
• Familiarity with data systems such as ELNs, LIMS, and software tools used to manage and analyze large analytical datasets.
• Ability to operate effectively in a fast-moving, innovative environment with evolving platform needs and cross-functional priorities.
• Strong scientific curiosity and interest in building next-generation analytical capabilities for molecular discovery.

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

Lila Sciences is hiring a Software Engineer to develop the next generation of Lab Instrument Integration Software, which is a foundational component of our AI-enabled laboratory. We are looking for self-motivated problem solvers who enjoy sitting at the often tricky interfaces between software, science, and hardware to deliver powerful solutions that will accelerate science.

What You'll Be Building

• Lab Instrument Software Development: Develop robust software to enable communication between robotics and automation hardware (e.g., robotic arms, liquid handlers, sensors) and the control software, ensuring reliable and efficient hardware integration.
• System Integration: Seamlessly integrate lab instruments into our Next Generation, AI-enabled lab automation infrastructure, managing complex interfaces between cloud and edge infrastructure, and device execution.
• Testing and Debugging: Perform rigorous testing, debugging, and troubleshooting of drivers to identify, isolate, and rectify performance issues, bugs, and compatibility challenges.
• Technical Documentation: Create, update, and maintain clear, comprehensive documentation for driver interfaces, APIs, and integration methods, facilitating ease of use by internal teams and end-users.
• Collaboration and Support: Work closely with cross-functional teams, including hardware engineers, software developers, product managers, and end-users, providing technical support and resolving integration challenges promptly.
• AI driven development: work with state of the art coding models and development infrastructure to improve the speed and quality of software delivery.

What You’ll Need to Succeed

• Proficiency in Python, C#/.NET, or other programming languages or frameworks is essential
• Demonstrated ability in debugging and problem-solving, preferably hardware-software integration issues.
• Strong analytical thinking and a structured approach to troubleshooting and resolving complex technical problems.
• Strong verbal and written communication skills to collaborate effectively with multidisciplinary teams.

Bonus Points For

• A strong interest in or background in science
• Experience in developing software for laboratory automation systems or robotics used in life sciences, pharmaceutical, or similar industries.
• Experience working directly with end-users (e.g., scientists, laboratory technicians), using feedback to drive product improvements.
• Experience with hardware integration and device driver development, especially in robotics or automation contexts.
• Proficiency with version control systems, especially Git.

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.

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

As Lila scales its AI Science Factories globally, the VP of Engineering will create and sustain an engineering model for a unified, scalable platform for autonomous experimentation. This role will be responsible for defining and implementing that platform across hardware, automation, and systems engineering. This executive will own strategy, execution, and talent across Lila’s systems, hardware, and automation engineering. The role sits on the senior leadership team, reports directly to the Chief Autonomous Science Officer, and interfaces directly with Robotics, Software, Operations, and Science teams.

The VP Engineering will bring deep technical experience in automation of lab science, a track record of building and leading multi-disciplinary engineering organizations, mentorship practices that foster career development of engineers at all levels, and the judgment to balance near-term delivery with long-term platform development. This is a hands-on leadership role in a fast-moving environment, requiring brilliance and dynamism to realize autonomous experimentation across materials science, chemistry, and life science. The role requires engineering innovations to achieve an unprecedented depth of AI integration in lab science, which combined with aggressive scaling of Lila’s AI Science Factories (AISFs) will produce the highest degree of scientific intelligence on earth.

What You'll Be Building

• Set the engineering roadmap for ASP Engineering, including objectives, risks, and platform priorities via collaboration with the Robotics, Software, Science, and Product teams.
• Define and drive a unified platform architecture across hardware, automation, and systems engineering, reducing one-off designs and enabling repeatable system deployment across sites
• Establish system-level ownership of architecture, interfaces, and requirements to ensure consistent integration across all engineering domains
• Implement efficient processes for lifecycle, design controls, safety and compliance, change management, and deployment of autonomous laboratories to support rapid scaling without compromising system consistency
• Develop a repeatable deployment model for standing up global AI Science Factory sites with predictable performance and reliability
• Create a culture of mentorship that supports execution of the roadmap while fostering career development of engineers
• Partner with Robotics and Software to build, industrialize, and scale all-of-science autonomous labs with a focus on reliability, throughput, and quality
• Integrate AI into the engineering lifecycle to bolster engineering speed and quality, decision making, and continuous improvement
• Collaborate with Talent Acquisition to establish hiring practices that accelerate identification and onboarding of brilliant, culturally-aligned engineers
• Partner with AI Research, Software, Product, and Science to align platform capabilities with scientific and commercial priorities
• Develop and communicate clear prioritization frameworks across engineering initiatives; translate organizational feedback into actionable systems and process improvements
• Represent Engineering with executive stakeholders and external partners; communicate tradeoffs, progress, and impact clearly
• Partnering with external integrators, OEMs, and contractors to expand engineering capacity

What You’ll Need to Succeed

• 15+ years building lab automation systems
• 10+ years leading managers and multi-disciplinary teams at scale
• Proven track record scaling automated labs or manufacturing-like lab operations, including instrument and robot integration, scheduling and orchestration, reliability engineering, and capacity planning
• Demonstrated experience integrating AI/ML into engineering, operations, and/or research environments
• Experience building and standardizing complex engineering systems from early-stage, project-based environments into scalable, repeatable platforms
• Demonstrated ability to balance rapid experimentation with the introduction of structure required for scale
• Technical expertise across lab automation, controls/SCADA, and science instrumentation, including integration and co-development of robotics and software/data/compute platforms
• Strong people and org leadership: recruiting and developing exceptional managers and ICs; building inclusive, high-ownership cultures that scale
• Excellence in retaining cultural and technical excellence across multiple sites of lab automation innovation and build-outs

Bonus Points For

• Multi-domain engineering excellence (mechanical, controls, electrical, systems) and cross-discipline engineering fluency (robotics, software, computer)
• Experience defining interface standards across hardware, robotics, and software systems
• Experience standing up lifecycle management (e.g., PLM-lite, change control, commissioning frameworks) in fast-moving environments
• Multi-domain science fluency (materials science, chemistry, life science)
• 10+ years experience integrating LIMS, orchestration, schedulers, and reliability and observability pipelines in lab automation
• Experience managing stage-gate transitions from R&D to scaled operations across multiple sites

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

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

The Director, Discovery Chemistry will lead the design, synthesis, and optimization of small molecules across Lila’s discovery platform, with a primary focus on organic synthesis, molecular design, and scalable chemistry execution. This leader will build and scale a world-class molecular chemistry program that translates AI-generated molecular hypotheses into high-quality, synthetically tractable, and functionally validated chemical matter.

Working closely with Lila’s AI, automation, computational, biology, and platform teams, this role will establish the chemistry infrastructure required to rapidly progress novel molecules from concept to validated candidates across a broad range of discovery efforts. The Director will drive synthetic strategy, route design, analog generation, molecular property optimization, and chemistry-enabled innovation, while enabling seamless integration with robotic synthesis and platform-based experimentation.

This leader will play a central role in shaping Lila’s molecular discovery engine by combining deep expertise in synthetic organic chemistry, molecular design, and data-enabled experimentation to accelerate the discovery of high-value molecules for therapeutic and broader platform applications.

What You'll Be Building

• Drive discovery chemistry strategy across discovery programs, with strong emphasis on small molecule design, synthetic innovation, analog generation, and optimization of chemical matter.
• Lead the design and execution of synthetic routes for novel small molecules, emphasizing speed, robustness, scalability, and compatibility with automated synthesis platforms.
• Develop and implement efficient workflows for molecular design, compound prioritization, analog generation, and iterative design–make–test cycles in collaboration with AI and computational teams.
• Partner closely with automation and platform teams to establish robotic and high-throughput chemistry capabilities that expand accessible chemical space and accelerate molecule generation.
• Guide the selection of reagents, reaction modalities, and synthetic methodologies to enable rapid exploration of structurally diverse and functionally relevant chemical matter.
• Drive discovery chemistry strategy across discovery programs, with strong emphasis on small molecule design, synthetic innovation, analog generation, and optimization of chemical matter.
• Lead the design and execution of synthetic routes for novel small molecules, emphasizing speed, robustness, scalability, and compatibility with automated synthesis platforms.
• Develop and implement efficient workflows for molecular design, compound prioritization, analog generation, and iterative design–make–test cycles in collaboration with AI and computational teams.
• Partner closely with automation and platform teams to establish robotic and high-throughput chemistry capabilities that expand accessible chemical space and accelerate molecule generation.
• Guide the selection of reagents, reaction modalities, and synthetic methodologies to enable rapid exploration of structurally diverse and functionally relevant chemical matter.
• Oversee molecular optimization by integrating chemistry principles including structure–activity relationships, physicochemical properties, selectivity, developability, and synthetic tractability.
• Collaborate with biology, screening, and profiling teams to interpret assay and characterization data and translate those insights into informed molecular design decisions.
• Drive discovery efforts from early chemical matter generation through optimization of advanced molecules, including scaffold evolution, property tuning, and progression toward candidate-quality compounds.
• Establish best practices for experimental design, chemistry data capture, compound registration, quality control, and reproducibility across molecular chemistry operations.
• Contribute strategically to program direction by aligning chemistry efforts with therapeutic hypotheses, platform capabilities, and broader company priorities.

What You’ll Need to Succeed

• PhD in Organic Chemistry, Medicinal Chemistry, Chemical Biology, or a closely related discipline with 12–15 years of experience in small molecule discovery and molecular design.
• Demonstrated experience building and leading high-performing chemistry teams, including hiring, mentoring, and developing scientists across multiple levels.
• Proven track record advancing small molecule programs through molecular design, high-throughput synthesis, optimization, and candidate progression.
• Deep expertise in synthetic organic chemistry, retrosynthesis, route design, and practical execution of complex multistep syntheses.
• Strong experience optimizing molecular properties, including potency, selectivity, physicochemical behavior, and overall developability of small molecule series.
• Demonstrated success designing and delivering compound libraries or analog series to efficiently explore chemical space and address multiparameter optimization challenges.
• Experience working effectively in highly interdisciplinary environments spanning chemistry, biology, automation, and computational sciences.
• Experience collaborating with biology, screening, pharmacology, or related functions to incorporate experimental data into chemistry decision-making.
• Strong understanding of compound quality standards, purification and characterization workflows, and chemistry data integrity.
• Track record of scientific leadership, program delivery, and advancing discovery-stage molecules in an industrial or high-performance research environment.

Bonus Points For

• Experience working in AI-enabled discovery environments or integrating computational design and machine learning insights into chemistry workflows.
• Experience building or scaling automated, robotics-enabled, or high-throughput chemistry platforms for molecular synthesis and optimization.
• Familiarity with modern synthesis-enabling technologies.
• Experience translating chemistry needs into platform requirements, including instrumentation selection, workflow design, and integration with automated systems.
• Broad understanding of molecular design principles across therapeutic discovery and other small-molecule innovation areas.
• Experience operating in fast-paced environments where scientific creativity, speed, and cross-functional execution are critical.
• Ability to evaluate synthetic feasibility alongside innovation potential to prioritize molecules and chemical series effectively.
• Strong communication and leadership skills, with the ability to align multidisciplinary teams around ambitious scientific goals.

Your Impact at LILA

Lila Sciences is seeking a relentless executor and strategic operator to spearhead our Instrument Development initiatives and lead our Virtual Lab Team. As the Director of Instrument Development Acceleration, you will be responsible for getting instruments online, fast, reliably, and at scale. The role is for someone who thrives in high-throughput environments and measures success in instruments shipped.

What You'll Be Building

• Set clear expectations, remove obstacles quickly, and keep the team focused on delivery over deliberation.
• Own the rapid design and development of laboratory instruments across the full lifecycle, from concept to operational in the lab, at high volume.
• Architect and implement integration frameworks connecting virtual laboratory environments with physical instrumentation and robotic systems.
• Maintain rigorous hardware-software integration standards, system performance benchmarks, and quality assurance processes without letting them become bottlenecks.
• Make pragmatic technical decisions across software, hardware, and systems integration that keep momentum, escalating only what truly needs escalation.
• Work tightly with AI researchers, software engineers, and robotics teams to drive fast, efficient system integration and deployment.
• Communicate clearly and concisely on status, blockers, and decisions to stakeholders at all levels.
• Build and refine lean development practices that prioritize speed, system reliability, and repeatable quality assurance.

What You’ll Need to Succeed

• Bachelor's or Master's degree in Computer Science, Engineering, Biomedical Engineering, or a related field. Ph.D. is a plus but not required.
• At least 10 years in engineering or technical leadership, with a proven record of delivering complex systems at scale and on time.
• Strong hands-on coding ability in C++, Python, or Java, with deep experience in hardware-software integration.
• Proven ability to lead complex systems integration across software, hardware, and robotic platforms.
• A problem-solver who makes decisions with imperfect information and keeps moving.
• Clear, direct communicator who can align engineers and stakeholders without unnecessary overhead.

Bonus Points For

• Experience with agile or lean development methodologies in high-throughput environments.
• Hands-on knowledge of AI, robotics, and simulation technologies as applied to laboratory instrumentation and automation.
• Experience with system monitoring, performance optimization, and QA in hardware-software environments.
• Track record of scaling teams and processes during periods of rapid growth.

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

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

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.

Why Join Us?

As a member of the Parabilis Medicines team, you will be a part of an organization dedicated to creating extraordinary medicines for diseases with urgent unmet needs, harnessing our proprietary peptide platform to transform treatment possibilities for patients. Parabilis is a clinical-stage biopharmaceutical company dedicated to unlocking high-impact protein targets long-considered undruggable. The company has developed a new class of stabilized, cell-penetrant alpha-helical peptides – Helicons™ – capable of modulating intracellular proteins that are inaccessible to traditional drug modalities.

Headquartered in Cambridge, Mass., Parabilis is advancing a focused pipeline of multiple first-in-class therapies across both rare and common cancers. Its lead asset, zolucatetide (FOG-001), is a first-in-class, clinically validated direct inhibitor of the interaction between β-catenin and the T-cell factor (TCF) family of transcription factors, implicated in millions of cancer cases annually, including in colorectal cancer, desmoid tumors, hepatocellular carcinoma and a range of other Wnt/β-catenin-driven tumors. In Phase 1 clinical trials, zolucatetide produced the first-ever clinical evidence that it can directly inhibit this interaction, once previously considered “undruggable” despite its role across multiple cancer types. Parabilis is also advancing investigational degraders of ERG and ARON into clinical development for the treatment of prostate cancer, as well as progressing other preclinical programs. Backed by a recent $305 million Series F financing, Parabilis is entering an exciting phase of growth and execution.

What’s the opportunity?

We are seeking a Scientist with a chemical biology mindset and strong experimental skills to help advance and scale our AI-driven peptide discovery programs. Parabilis has built a powerful high-throughput mass-spec driven multiplexed screening platform that enables us to navigate chemical space and optimize our Helicons to target undruggable proteins. In this role, you will develop and improve experimental methods for understanding Helicon activity and properties, leveraging a range of laboratory and computational tools, and collaborating as part of a cross-functional team. Over time, you will develop an understanding of Helicon design and leverage high-quality assay data to advance drug discovery programs.

Specific responsibilities include:

• Develop and improve experimental screening assays: design, optimize, and productionize biochemical and cell-based assays that allow us to measure drug-like properties at scale across multiple programs.
• Advance automation in practice: implement automation for existing assays, and construct new assays with laboratory robotics in mind, troubleshooting and iterating workflows to achieve consistent performance and to facilitate integration with digital and AI/agent-driven automation.
• Build script-based tools to scale execution: develop reusable scripts and lightweight tools that reduce manual steps and improve experiment setup, tracking, QC, and reporting for broad team use.
• Drive decision-quality data and learning: apply quantitative rigor to assay performance and data QC and translate outputs into insights that inform next experiments and, over time, Helicon optimization.  
  

What you’ll need to be successful:

Required qualifications

• PhD in Chemical Biology, Biochemistry, Cell Biology, or a related discipline, with 2-4 years of postdoctoral and/or industry experience.
• Strong hands-on experience developing, optimizing, and executing experimental assays (biochemical, biophysical, and/or cell-based), with demonstrated ability to translate complex biological questions into robust, scalable assay formats.
• Quantitative approach to assay quality and performance, including comfort with controls, variability, robustness, and data QC to produce decision-quality readouts.
• Demonstrated scripting and tool-building experience beyond ad hoc “vibe coding,” with examples of using code to automate analyses, streamline workflows, or solve recurring operational problems.
• Ability to work cross-functionally and communicate clearly with chemistry, biology, and data-focused colleagues.
• Demonstrated use of AI tools in your current role and responsibilities is required; advanced or innovative use is a plus.

Preferred qualifications

• Experience improving lab throughput through automation or semi-automation, or strong aptitude and interest in learning and applying automation technologies in a screening environment.
• Familiarity with high-throughput screening concepts and scaling assay workflows to support large sample numbers.
• Working knowledge of peptide chemistry and/or peptide discovery concepts is a plus but not required.

Ways of working that matter here

• A builder mindset with strong scientific judgment: you identify bottlenecks, choose the least-resistant path to improvement, and execute with urgency.
• Curiosity for emerging technologies and a practical approach to evaluating what could improve workflow robustness, automation, or assay quality.
• Highly collaborative, low-ego, can-do attitude with consistent follow-through and strong ownership of results.

Core Values

Parabilis is a team of passionate pioneers who are trailblazing the future of precision medicine with the aim of making a meaningful difference in the lives of patients. The company is committed to promoting an inspiring and flourishing working environment for all employees across the business, in all departments, and driving innovation for patient benefit.

• Growth-Minded. We’re inventing a new class of medicines—one applicable to therapeutic targets that have been dreamt about, but always considered impossible to drug. Our work requires us to be curious, humble and adaptable.
• In(ter)dependent. We are fiercely independent as a leader in defying the limitations of current therapeutic modalities, and interdependent as a team as we work collaboratively to shift drug discovery paradigms and provide patients with better treatment options.
• Patient-focused. We are deeply focused on patient outcomes, and all energy in the company is focused on science as it translates to patient impact.
• All-In. We’re All-In on solving some of the hardest scientific challenges and delivering one of the most effective new classes of drugs in history.

The base salary range for this position is [$120,000–$145,000] per year, depending on experience, qualifications, and internal practices. Parabilis’s total compensation package also includes an annual target bonus, equity, and a comprehensive suite of competitive benefits designed to support our employees’ overall well-being.

As an equal opportunity employer, Parabilis values an inclusive workplace and welcomes applicants of all backgrounds and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other factors prohibited by law.

Why Join Us?

Parabilis Medicines is a clinical-stage biopharmaceutical company dedicated to creating extraordinary medicines that unlock high-impact protein targets long-considered undruggable. The company has developed a new class of stabilized, cell-penetrant alpha-helical peptides – Helicons™ – capable of modulating intracellular proteins that are inaccessible to traditional drug modalities. 

Headquartered in Cambridge, Mass., Parabilis is advancing a focused pipeline of multiple first-in-class therapies across both rare and common cancers. Its lead asset, zolucatetide (FOG-001), is a first-in-class, clinically validated direct inhibitor of the interaction between β-catenin and the T-cell factor (TCF) family of transcription factors, implicated in millions of cancer cases annually, including in colorectal cancer, desmoid tumors, hepatocellular carcinoma and a range of other Wnt/β-catenin-driven tumors. In Phase 1 clinical trials, zolucatetide produced the first-ever clinical evidence that it can directly inhibit this interaction, once previously considered “undruggable” despite its role across multiple cancer types. Parabilis is also advancing investigational degraders of ERG and AR^ON into clinical development for the treatment of prostate cancer, as well as progressing other preclinical programs. Backed by a recent $305 million Series F financing, Parabilis is entering an exciting phase of growth and execution.

What’s the opportunity?

The Research Equipment Lead is responsible for enabling Parabilis’ cutting-edge research by ensuring laboratory equipment is strategically selected, optimally configured, highly reliable, and continuously improving. This role owns the full lifecycle of research instrumentation and partners closely with Research, Finance, Facilities, IT, Quality, and external vendors to minimize downtime, enable automation, and support scalable, reproducible science.

This position requires deep and broad technical expertise across research equipment platforms, strong operational rigor, and the ability to integrate automation, data, and AI-driven approaches into lab operations. The Research Equipment Lead plays a critical role in aligning equipment strategy with scientific roadmaps, growth plans, and financial and regulatory requirements.

Equipment Lifecycle & Operational Excellence

• Own the full lifecycle of research equipment, from needs assessment and acquisition through installation, operation, maintenance, and retirement, ensuring high availability and performance across research groups.
• Oversee day-to-day equipment operations, including troubleshooting, repairs, and preventive maintenance programs to minimize downtime and disruption to research.
• Lead installation, qualification, validation, and calibration of laboratory instruments in coordination with vendors, Facilities, IT, and internal stakeholders, applying continuous improvement principles.
• Maintain comprehensive, audit-ready documentation, including equipment inventories, maintenance logs, calibration records, service contracts, and validation documentation, in alignment with internal policies and applicable regulatory expectations.
• Establish and monitor key performance indicators (KPIs) for equipment reliability, utilization, and downtime.

Training, Partnership & Vendor Management

• Serve as the primary point of contact for equipment-related issues across research labs.
• Develop and deliver technical training to ensure safe, effective, and compliant use of laboratory instruments.
• Build strong cross-functional partnerships with Research, Facilities, IT, Quality, Procurement, and Finance to ensure seamless equipment support and alignment.
• Manage vendor relationships, including service agreements, performance reviews, and escalation of technical issues.

Equipment Strategy, Automation & Capital Planning

• Partner with R&D leadership to forecast equipment, automation, and digital infrastructure needs aligned with scientific strategy, growth plans, and budget constraints.
• Collaborate with Finance on capital planning, asset tracking, depreciation, and accounting requirements for research equipment.
• Evaluate emerging technologies, automation platforms, and AI-enabled tools; recommend capital investments that improve efficiency, scalability, data quality, and reproducibility.
• Identify opportunities to implement laboratory automation, robotics, and software-driven workflows, including the use of AI or data analytics to optimize equipment performance, scheduling, predictive maintenance, and experimental throughput.
• Contribute to the design or customization of novel or integrated instrumentation solutions to support next-generation research.

What you’ll need to be successful:

• Bachelor’s degree in Engineering, Life Sciences, Chemistry, Physics, or a related technical discipline; advanced degree preferred.
• 5-7+ years of hands-on experience supporting and maintaining complex research laboratory equipment across multiple scientific functions.
• Demonstrated expertise in equipment lifecycle management, preventive maintenance programs, and vendor coordination.
• Working knowledge of relevant scientific, engineering, operational, safety, and regulatory principles applicable to research laboratories.
• Strong organizational skills with exceptional attention to detail and documentation rigor.
• Proven ability to collaborate cross-functionally and communicate effectively with technical and non-technical stakeholders.
• Experience implementing laboratory automation, robotics, or digitally enabled workflows.
• Familiarity with AI- or data-driven approaches to equipment monitoring, utilization, or predictive maintenance.
• Experience partnering with Finance on capital equipment planning, budgeting, and accounting processes preferred.
• Demonstrated ability to utilize AI tools for day-to-day work; baseline proficiency is expected, and advanced or innovated use of AI is a strong plus
• Able to work on-site and attend in-person meetings

Core Values

Parabilis is a team of passionate pioneers who are trailblazing the future of precision medicine with the aim of making a meaningful difference in the lives of patients. The company is committed to promoting an inspiring and flourishing working environment for all employees across the business, in all departments, and driving innovation for patient benefit.

• Growth-Minded. We’re inventing a new class of medicines—one applicable to therapeutic targets that have been dreamt about, but always considered impossible to drug. Our work requires us to be curious, humble and adaptable.
• In(ter)dependent.We are fiercely independent as a leader in defying the limitations of current therapeutic modalities, and interdependent as a team as we work collaboratively to shift drug discovery paradigms and provide patients with better treatment options.
• Patient-focused.We are deeply focused on patient outcomes, and all energy in the company is focused on science as it translates to patient impact.
• All-In.We’re All-In on solving some of the hardest scientific challenges and delivering one of the most effective new classes of drugs in history.

The base salary target for this position is $86,000-$110,000 per year, depending on experience, qualifications, and internal practices. Parabilis’s total compensation package also includes an annual target bonus, equity, and a comprehensive suite of competitive benefits designed to support our employees’ overall well-being.

As an equal opportunity employer, Parabilis values an inclusive workplace and welcomes applicants of all backgrounds and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other factors prohibited by law.

At Charles River Analytics, we develop leading-edge solutions and technology to address the world’s most complex challenges. Our team of innovative entrepreneurs drives advancements in AI, robotics, smart sensing, and human-centered computing. Our research and development efforts not only propel government programs forward but also unlock new opportunities in the commercial sector. As a 100% employee-owned company, we foster a culture of participation, innovation, and accountability among our staff. We take immense pride in our ability to attract and retain the industry's most talented and creative problem solvers.

We are looking for enthusiastic engineering and research interns to join the Charles River Analytics 2026 summer intern program. This is a great opportunity to gain hands on industry experience and join a highly innovative research and development team this summer!

We are in search of students with interests in:

• Software Engineering
• Artificial Intelligence
• Machine Learning
• Natural Language Processing 
• Computer Vision, Autonomy, and Robotics
• Probabilistic Programming
• Human Computer Interaction
• Adaptive Intelligent Tutoring

What do you need?

• U.S. Citizenship
• Currently in pursuit of a B.S., M.S., or Ph.D in a computer science related program
• Available for a 2026 summer internship
• Ability to work on multiple projects, switching easily from task to task and learning new concepts as necessary
• Experience with a high-level programming language and a solid background in designing, programming, and documenting complex software systems
• Code and writing samples may be requested

Benefits:

Charles River Analytics offers an attractive benefits package that includes, but is not limited to the following:

• Casual work environment
• Free snacks and beverages
• Eligible for medical plan enrollment or opt-out incentive
• Paid sick/excused time
• Free onsite parking and easily accessible by the MBTA

Internship Activities:

Interns at Charles River Analytics can participate in activities such as:

• Intern challenge problems
• Seminars
• Company-wide outings

You can learn more about our internship program here as well as check out last year’s Great Promise Award (GPA) winners to hear what it is like to be an intern at Charles River Analytics!