Your Impact at LILA

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

What You'll Be Building

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

What You’ll Need to Succeed

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

Bonus Points For

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

Your Impact at LILA

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

What You'll Be Building

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

What You’ll Need to Succeed

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

Bonus Points For

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

Title:                   Contract - Senior Clinical Trial Associate

Location:           Cambridge, MA, Hybrid, or Remote

Reports to:        Head of Clinical Operations

About Vedanta Biosciences:

Vedanta Biosciences is a late-stage biopharmaceutical company developing medicines for the treatment of gastrointestinal diseases. The company’s lead assets include potential first-in-class oral therapy, VE303, in a Phase 3 trial for recurrent C. difficile infection. Vedanta’s pipeline has been built using the company’s industry-leading product engine for the development of therapies based on defined consortia of bacteria grown from pure clonal cell banks. The product engine, supported by foundational IP, includes one of the largest libraries of bacteria isolated from the human microbiome, vast clinical datasets, proprietary capabilities in consortium design, and end-to-end CGMP manufacturing capabilities at commercial launch scale.

The Role:

The Senior Clinical Trial Associate is a key member of the Clinical Operations and clinical project teams. The Sr. CTA acts as a central contact and hub for the clinical study team and in this capacity supports the team in the planning, implementation, completion, and wind down of clinical trial(s). This individual will work and partner with both internal and external stakeholders, namely investigative sites, vendors, and team members.

Here’s What You’ll Do:

• Set up, maintain, reconcile, and archive electronic and paper Trial Master Files
• Coordinate TMF transfer with CROs
• Assist with auditing and reconciling all study-related documents for clinical studies
• Work closely with the Study Team Leader and coordinate, track, and manage logistics in support of studies
• Track study status, enrollment, regulatory documentation, laboratory samples, and site start-up status for assigned clinical projects
• Actively order and maintain ancillary clinical study supplies required for the conduct of clinical studies
• Help in planning, preparing, and distributing materials for study meetings
• Prepare agenda and meeting minutes for internal and external meetings as requested
• Assist Study Team Leader with reporting benchmark metrics to senior management
• Contribute to the preparation of presentations and reports as required
• Assist with archiving study documents for completed clinical studies
• Perform additional tasks as requested

Requirements:

• Bachelor’s degree
• 5+ years of relevant hands-on study experience in clinical research, ideally within a sponsor setting
• Exceptional communication (oral and written), organizational, and problem-solving skills
• Excellent Microsoft Office skills
• High-energy individual able to effectively multi-task and strive in a dynamic start-up environment
• Strong attention to detail
• Solid knowledge of GCP guidelines and other regulatory requirements for clinical trial management

The base pay range for this position is expected to be $48-55 hourly; however, the base pay offered may vary depending on market dynamics, experience, internal equity, and job-related knowledge, skills, and capabilities.

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?

The Vice President, Medical Affairs Oncology is a member of the Development Leadership Team reporting to the Chief Medical Officer. This senior executive leader is accountable for the end-to-end design and execution of the Medical Affairs strategy across Parabilis portfolio, including Scientific Communications, Medical Education, Evidence Generation, Key Opinion Leader (KOL) Engagement, Publication Planning, and Medical Information. This role ensures scientific excellence and cross-functional integration across all development programs and builds a scalable Medical Affairs organization capable of supporting global, multi-indication growth.

Key Responsibilities:

Strategic Leadership

• Define and execute the Medical Affairs Oncology strategy aligned with the clinical development roadmap and portfolio priorities.
• Serve as a core member of the Development Leadership Team and contribute to broader
• Development governance and portfolio decision-making.
• Support portfolio-level medical prioritization, lifecycle planning, and cross-indication strategy.

KOL Engagement & Medical Education

• Build and sustain relationships with leading KOLs, academic medical centers, and cooperative groups relevant to Parabilis’ pipeline.
• Design and oversee Medical Education programs that advance understanding of Parabilis’ science, novel mechanisms, and unmet need across tumor types.

Evidence Generation & Publication Strategy

• Lead the development and execution of a robust evidence generation strategy, including investigator-initiated studies, real-world evidence, and health outcomes research
• Oversee development and execution of a comprehensive publication plan aligned with clinical milestones and regulatory timelines
• Build global medical affairs infrastructure to support multi-program, multi-regional growth
• Drive Medical Affairs KPIs and impact metrics in support of portfolio strategy and commercial readiness

Scientific Communications & Medical Information

• Lead scientific communications strategy to accurately and compellingly convey the differentiated profile of Parabilis’ Helicon™ platform and pipeline assets
• Oversee Medical Information function, ensuring timely, accurate, and compliant responses to healthcare professional inquiries
• Oversee the creation of high-quality medical education materials, slide decks, and scientific exchange resources
• Establish scalable medical affairs infrastructure to support launch readiness across tumor types and geographies

Patient Advocacy and Patient Support

• Building trusted partnerships with advocacy organizations across Parabilis' specific tumor types
• Integrating the patient voice into MA strategy, trial design, and evidence generation
• Collaborating with patient communities on disease awareness and education
• Developing patient support programs to improve access, adherence, and trial participation ensuring all patients’ engagement is conducted with ethical rigor and full compliance

Cross-functional Partnership & Commercial Readiness

• Partner closely with Clinical Development, Regulatory Affairs, and New Product Planning to ensure scientific and medical alignment across the development and pre-commercialization continuum
• Support payer strategies by contributing to value dossiers, HEOR data packages

Compliance & Medical Governance

• Lead development and continuous improvement of Medical Affairs SOPs, governance frameworks, and compliance systems
• Ensure all Medical Affairs activities are executed in accordance with applicable regulations, industry codes, and Parabilis’ internal policies

Organizational Leadership

• Build and mentor a high-performing Medical Affairs Oncology team with deep scientific expertise and strong cross-functional collaboration skills
• Establish clear accountability, performance metrics, and a culture of scientific rigor and integrity
• Foster a culture of collaboration, scientific curiosity, and patient-centricity across the Medical Affairs team

What you’ll need to be successful:

• MD required; PharmD or PhD in a relevant biomedical discipline may be considered with commensurate experience
• 15+ years of progressive biopharmaceutical industry experience, with a minimum of 8 years in Medical Affairs with deep scientific expertise in oncology
• Demonstrated success building and leading Medical Affairs organizations, including KOL engagement, evidence generation, and scientific communications
• Experience standing up Medical Affairs capabilities in high-growth, clinical-stage biotech or pharmaceutical environments
• Strong scientific credibility, executive leadership presence, and ability to engage effectively with both internal and external stakeholders
• High emotional intelligence and track record of cross-functional influence across Development, Commercial, and Regulatory functions

Core Values

Parabilis Medicines 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 $360,000-$410,000 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 Medicines 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.

30 Acorn Park Drive    |     Cambridge, MA 02140    |    www.parabilismed.com

The Opportunity

This Real World Evidence (RWE)/Health Economics (HEOR) Contractor role supports the RWE/HEOR Senior Director in leading RWE execution for pipeline assets. The role is fun and flexible with a mix of both study execution and data analytics. This person will be accountable for developing and delivering components of the evidence generation plan (including RWE and economic value evidence), and driving high-quality deliverables that inform internal decision-making during product development, pre-launch readiness, and lifecycle planning. The role is anchored to 1–2 priority pipeline assets/indications.

This is a remote role based with flexible hours. We are currently seeking an individual with 20-30 hours of weekly availability with potential to increase hours in late 2026/2027.

Responsibilities

• Evidence strategy and planning: Maintain US RWE & HEOR plans for 1–2 priority pipeline assets/indications, aligned to US medical, payer, and access needs; translate strategy into actionable workplans, timelines, and resourcing proposals.
• Study leadership (RWE/HEOR): Own day-to-day leadership for assigned real-world evidence and health outcomes studies (e.g., real-world evidence studies, cost-effectiveness/budget impact analyses, burden of illness, treatment patterns, patient-focused outcomes) including design and execution in partnership with internal functions and external vendors.
• Scientific communication and quality: Draft/review project specifications, protocols, statistical analysis plans, study reports, abstracts, posters, and manuscripts; ensure adherence to SOPs and high scientific/operational quality.
• Analytic execution and statistics: Execute ad hoc analyses in clinical trial, claims and PCOR data as needed for ad hoc and protocol/SAP driven analyses. This may include feasibility or full protocol execution.
• Governance, compliance, and capability building: Complete required training, adhere to company/department SOPs, and contribute to continuous improvement of processes that enable efficient planning, execution, and dissemination of RWE & HEOR deliverables.

Required Qualifications

• Master’s degree or PhD in epidemiology, health economics and outcomes research, public health, biostatistics, or related discipline.
• At least 1+ years of experience in the pharmaceutical industry and/or managed care, hospital, academic, or healthcare consulting environment with exposure to HEOR/RWE strategy and application
• Proficiency with SAS and/or R for statistical programming. Preference for experience in clinical trials OR claims data.
• Expertise in RWE and study designs/methods evidenced by publications and/or contributing to study concept sheets and protocols, reviewing/authoring key sections of statistical analysis plans and study reports, and ensuring publication/disclosure readiness in accordance with ICJME criteria
• Strong communication and presentation skills, demonstrated by developing and presenting clear, decision-oriented materials (e.g., evidence strategy slides, executive readouts) and summarizing outcomes/next steps for senior audiences

Preferred Qualifications

• Demonstrated success developing and executing health outcomes research plans and delivering high-quality data generation outputs.
• Experience managing real-world data sources and vendors (e.g., claims, EHR, registries) and translating findings into actionable insights and value messages.
• Demonstrated ability to influence without authority in a matrix environment, evidenced by aligning cross-functional stakeholders on objectives/trade-offs, documenting decisions, and driving actions to closure.
• Experience in PCOR implementation and validation

Work Location and Condition

• At Amylyx, we proudly support remote work opportunities within the United States. However, due to business considerations related to health insurance coverage and state tax regulations, we are unable to hire employees who reside and/or work in certain states. Currently, we are not considering applicants from Alaska, Arizona, Hawaii, Michigan and Tennessee.
• You must have access to work in setting that meets all requirements of the role (including privacy, reliable internet access, phone, ability to communication via video conference, etc.) at your remote location

Position Summary:

The Senior Director, Commercial Strategy lead is responsible for understanding the evolving needs of the Stargardt community and shaping the brand strategy, including the execution of comprehensive marketing plans. This role will lead brand planning, product launches, and lifecycle management, working closely with cross-functional teams across commercial, medical, regulatory, and clinical functions.

This is a leadership role on the commercial team that will own the go-to-market strategy, lifecycle planning, ensuring seamless collaboration across functions and support market access research ultimately driving meaningful patient impact and delivering strong business results.

Primary Responsibilities:

Brand Strategy & Tactical Execution:

• Develop integrated brand strategies and lifecycle activities to support differentiation and commercialization goals
• Drive disease area strategy, market segmentation, and product positioning based on unmet needs, competitive landscape, and evolving science
• Responsible for creating external (promotional/educational) communication materials for external use with customers (ECPs and Patients)
• Partner with Corporate Communications to support development of the Corp Communications tactics and messages as needed
• Lead the cross-functional workshops for the development of strategic and tactical plans for gildeuretinol

Competitive Strategy and Response:

• Assess emerging trends, market dynamics, and competitive activity to inform commercial decisions
• Lead competitive scenario planning and collaborate with medical, corp. comms, strategic planning and clinical to develop competitive response strategy
• Translate scientific and market insights from ECPs and patients (through market research, ad boards, etc.) into differentiated product strategy and value stories
• Evaluate strategic implications of evolving regulatory, pricing, and access landscapes globally
• Provide input into forecasting assumptions and evaluate ROI for activities
• Collaborate closely with regulatory, medical affairs, market access and corporate communications to ensure alignment of brand vision and execution

Program Team and key workstreams participation:

• Lead development/optimization of TPP
• Generate and communicate ECP/Patient insights to inform Program strategy
• Be the commercial voice on program team and inform decisions impacting commercialization
• Participate in the evidence generation, pubs planning and LCM strategy sub teams to represent the commercial POV

Qualifications:

• Education and Certification
• Advanced degree (MBA) in marketing/ business, or scientific degree preferred
• Requires 12+ years of experience or the equivalent combination of education and experience

• Skills and Key Success Factors:
  • Entrepreneurship spirit with a passion to build, learn and evolve with the team
  • Highly organized and detail oriented with a passion to deliver quality results
  • Excellent verbal and written communication skills, with experience translating complex concepts for various audiences
  • Demonstrated record of intellectual curiosity, innovation and creative problem solving with an entrepreneurial spirit
  • Ability to lead fast-paced projects with a keen sense of urgency to get the job done well
  • Evidence of "hands-on" experience and expertise
  • Proven and successful track record as a team-player and collaborator in small working environments
  • Highest levels of professionalism, confidence, personal values and ethical standards

Other Relevant Information:

• Travel:  Able to travel up to 25% of time

Compensation

• Base Salary Range: $235K - $275K, with the actual contingent upon several factors such as the selected candidate’s education/work experience/training, and other factors (travel requirements, etc.)
• Discretionary Bonus: up to 25% of Base Salary, contingent upon meeting performance components
• Equity: initial grant of incentive stock options
• Benefits: Eligible to participate in group medical/dental/vision insurance plans; short- and long-term disability plans; life insurance; 401(K) plan; flexible time off policies and others. Eligibility and participation requirements vary by plan.

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 an experienced leader in vivarium and in vivo operations to oversee our research animal facilities and in vivo study support. In this Associate Director role, you will be accountable for daily operations, resource planning, budgets, technical training and compliance with IACUC, AAALAC and institutional policies. 

You will manage animal procurement, housing, husbandry services and technicalsupport across discovery and pre‑clinicalstudies, collaborating with program leaders and CRO partnersto align operationalsupport with scientific objectives. A key aspect of this role is developing and coaching a high‑performing technical team while driving operational excellence and continuous improvement to uphold the highest standards of animal welfare.

Key abilities of this role include:

• Provide strategic and operational leadership for vivarium operations, ensuring high-quality husbandry, facility maintenance, and resource planning.
• Serve as institutional lead for IACUC protocols and animal use compliance; prepare and lead facility audits and inspections.
• Oversee procurement and inventory of animals and supplies and maintain accurate records of census and environmental conditions.
• Develop and manage the vivarium operating budget, forecasting resource needs and supporting capital planning. 
• Provide oversight and coordination of in vivo hands on training and SOP adherence for a cross functional group of hybrid scientists; remain willing to perform hands on work as needed and lead the integration of new skills and techniques as our portfolio and programs expand. 
• Coordinate study scheduling and operational support across in vivo pharmacology programs and CRO partners; represent in vivo operations in cross-functional meetings.
• Drive process improvement, SOP development and emergency preparedness; ensure compliance with AAALAC and institutional policies.
• Provide subject matter expertise in in vivo study execution, facility operations, and support program teams by troubleshooting logistics.

What you’ll need to be successful:

• Bachelor’s or master’s degree in biological sciences, animal science or related discipline; 10+ years of vivarium/in vivo experience including 5+ years in a leadership role; advanced degree (M.S., DVM or Ph.D.) and AALAS/CMAR certification are preferred.
• Demonstrated success managing vivarium operations, including budgets, resource forecasting, animal procurement and facility maintenance.
• In depth knowledge of AAALAC and IACUC regulations and experience serving as institutional lead for animal use protocols and facility audits.
• Proven ability to supervise, mentor, and develop technical staff and maintain high standards of animal welfare and safety.
• Strong operational planning, problem-solving and process improvement skills, with experience developing SOPs and emergency plans. 
• Excellent communication and interpersonal skills and ability to collaborate across cross functional program teams and with CRO partners.
• Ability to thrive in a fast paced, collaborative environment, work on site and participate in weekend or holiday coverage as needed.

Core Values

Parabilis Medicines 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 $165,000-$200,000, 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 Medicines 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.

30 Acorn Park Drive    |     Cambridge, MA 02140    |    www.parabilismed.com

HubSpot welcomes individuals to join our Sales team as a Business Development Representative (BDR). As part of our commitment to building a hybrid company, BDRs can be flexible with their work location with the choice to either be based in Cambridge, Massachusetts, or remotely in the US. 

🚀 Join HubSpot as an Outbound Business Development Representative (BDR)
📍 Cambridge, MA or Remote (US)

We’ll be honest — sales isn’t easy, and it’s not for everyone. But for those who love a challenge, thrive on results, and want to launch a long-term path in sales, it’s incredibly rewarding.

If you’re looking to “try out” sales or just dip a toe in, this probably isn’t the role for you. But, if you’re the kind of person who wakes up hungry to compete, thrives on setting and smashing goals, and wants to build a career in tech sales from the ground up — we want to talk to you.

At HubSpot, our BDRs are not only the first point of contact for our prospects—they’re also developing the skills and mindset to become our next generation of Account Executives. This is not a placeholder job — it’s the first chapter of a high-growth sales career designed for those who want to build skills, embrace feedback, move fast, and grow even faster.

The Role:
As an Outbound BDR, you’ll play a key role in HubSpot’s growth engine. You'll be the first touchpoint for many of our future customers, sparking conversations through strategic outreach, uncovering pain points, and qualifying leads. You’ll partner closely with Account Executives to deliver high-quality meetings that drive pipeline, impact, and revenue. Along the way, you’ll sharpen your sales toolkit daily and gain exposure to a world-class sales organization.

What You’ll Do:

• Own and execute outbound prospecting through high-volume outreach (60–100+ activities/day) via phone, email, and LinkedIn.
• Collaborate with Account Executives to target strategic accounts and refine outreach strategy.
• Qualify leads based on fit, need, and urgency — and book quality discovery meetings.
• Hit (and exceed) KPIs for activity, meetings delivered, and pipeline impact.
• Grow fast. Learn fast. Get coached. Apply it. Repeat.
  
  

What You Won’t Do:

• Coast. We move fast, we test, we iterate, and we compete.
• Wait for someone to tell you what to do. We value self-starters who take ownership.
• Treat this as “just a job.” This is a foundational role, setting you up for a successful long term career in sales.
  
  

We’re Looking For People Who:
✅ Are eager to grow long-term within a sales path–if your focus is split between sales and other paths like customer success, marketing, operations, etc, this role likely won’t be the best fit.
✅ Are resilient, coachable, and crave feedback to improve.
✅ Are curious and ask why, not just how.
✅ Set high standards for themselves — and hit them.
✅ Are technologically fluent, adapting to new technologies and leveraging AI in your day-to-day.
✅ Communicate clearly, write thoughtfully, and can confidently conduct a cold call.
✅ Are energized by a fast-paced environment and a bit of friendly competition.
✅ Either have past sales success or have demonstrated excellence in goal-driven roles (think: fundraising, athletics, service industry, etc).

Tools We Use (and You’ll Learn):

• HubSpot (of course)!
• LinkedIn Sales Navigator
• AI Powered Tools across all aspects of the role for research & outreach
• Slack, Zoom, LeadIQ, Google Suite, Zoominfo, and more
  
  

To Apply:
📝 No cover letter required.
📄 Submit your resume.
👉 If you're new to sales, show us your grit: include examples of how you've hit ambitious goals in other roles.
📊 If you’ve been in sales before, highlight metrics like quota attainment.

Important information about the position.

Bottom Line:
We’re looking for future stars, not just seat-fillers. If you want to grow into an elite sales professional and are ready to work hard, get uncomfortable, and see what you're really capable of — this is your shot.

HubSpot welcomes individuals to join our Sales team as a Business Development Representative (BDR). As part of our commitment to building a hybrid company, BDRs can be flexible with their work location with the choice to either be based in Cambridge, Massachusetts, or remotely in the US. 

🚀 Join HubSpot as an Outbound Business Development Representative (BDR)
📍 Remote (US) or Cambridge, MA

We’ll be honest — sales isn’t easy, and it’s not for everyone. But for those who love a challenge, thrive on results, and want to launch a long-term path in sales, it’s incredibly rewarding.

If you’re looking to “try out” sales or just dip a toe in, this probably isn’t the role for you. But, if you’re the kind of person who wakes up hungry to compete, thrives on setting and smashing goals, and wants to build a career in tech sales from the ground up — we want to talk to you.

At HubSpot, our BDRs are not only the first point of contact for our prospects—they’re also developing the skills and mindset to become our next generation of Account Executives. This is not a placeholder job — it’s the first chapter of a high-growth sales career designed for those who want to build skills, embrace feedback, move fast, and grow even faster.

The Role:
As an Outbound BDR, you’ll play a key role in HubSpot’s growth engine. You'll be the first touchpoint for many of our future customers, sparking conversations through strategic outreach, uncovering pain points, and qualifying leads. You’ll partner closely with Account Executives to deliver high-quality meetings that drive pipeline, impact, and revenue. Along the way, you’ll sharpen your sales toolkit daily and gain exposure to a world-class sales organization.

What You’ll Do:

• Own and execute outbound prospecting through high-volume outreach (60–100+ activities/day) via phone, email, and LinkedIn.
• Collaborate with Account Executives to target strategic accounts and refine outreach strategy.
• Qualify leads based on fit, need, and urgency — and book quality discovery meetings.
• Hit (and exceed) KPIs for activity, meetings delivered, and pipeline impact.
• Grow fast. Learn fast. Get coached. Apply it. Repeat.
  
  

What You Won’t Do:

• Coast. We move fast, we test, we iterate, and we compete.
• Wait for someone to tell you what to do. We value self-starters who take ownership.
• Treat this as “just a job.” This is a foundational role, setting you up for a successful long term career in sales.
  
  

We’re Looking For People Who:
✅ Are eager to grow long-term within a sales path–if your focus is split between sales and other paths like customer success, marketing, operations, etc, this role likely won’t be the best fit.
✅ Are resilient, coachable, and crave feedback to improve.
✅ Are curious and ask why, not just how.
✅ Set high standards for themselves — and hit them.
✅ Are technologically fluent, adapting to new technologies and leveraging AI in your day-to-day.
✅ Communicate clearly, write thoughtfully, and can confidently conduct a cold call.
✅ Are energized by a fast-paced environment and a bit of friendly competition.
✅ Either have past sales success or have demonstrated excellence in goal-driven roles (think: fundraising, athletics, service industry, etc).

Tools We Use (and You’ll Learn):

• HubSpot (of course)!
• LinkedIn Sales Navigator
• AI Powered Tools across all aspects of the role for research & outreach
• Slack, Zoom, LeadIQ, Google Suite, Zoominfo, and more
  
  

To Apply:
📝 No cover letter required.
📄 Submit your resume.
👉 If you're new to sales, show us your grit: include examples of how you've hit ambitious goals in other roles.
📊 If you’ve been in sales before, highlight metrics like quota attainment.

Important information about the position.

Bottom Line:
We’re looking for future stars, not just seat-fillers. If you want to grow into an elite sales professional and are ready to work hard, get uncomfortable, and see what you're really capable of — this is your shot.

MORSE is searching for an experienced Data Scientist with expertise in data analysis, data science, and algorithm development in one or more of a variety of fields including visual classification, big data, natural language processing, machine translation, time sequenced data, and advanced metrics. You will be part of teams performing Test and Evaluation (T&E) of AI and machine learning models and algorithms to give national security customers insights into the capabilities of applying AI to solve real world problems.

Responsibilities:

• Perform data analysis, test and evaluation of existing machine learning algorithms, and development of advanced algorithms to model physical and autonomous systems,

• Work with MORSE’s current team of engineers to transition algorithms to software applications and real-time embedded systems.

• Support the transition of the developed algorithms to software using one or more programming languages such as Python, C, C++, Java, or MATLAB.

• Work with customers, stakeholders, and other vendors to present concepts, analyses, and test results

• Present a path forward and solutions to solve complex data problems

• Research and identify new methods for machine learning and data analysis

Requirements:

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

• Masters or Ph.D in Data Science, Computer Science, Engineering, Applied Mathematics, Physics, Physical or Biological Sciences or a related field

• 5+ years of experience in Data Science or Analysis

• Solid understanding of data analysis, physics, linear algebra, statistics, algorithms, optimization, and/or machine learning methods

• Proficiency in one or more programming languages like Python, Matlab, C, or C++

• Demonstrated experience with large, multidimensional, or complex data sets in one or more of the following areas: parsing, cleaning, storage strategies, provenance tracking, database formats, and parallelized data transformations

• Good communication skills

• Self-starter and driven

• Prior experience in defense is a plus

MORSE is searching for a Data Scientist with expertise in data analysis, data science, and algorithm development in one or more of a variety of fields including visual classification, big data, natural language processing, machine translation, time sequenced data, and advanced metrics. You will be part of teams performing Test and Evaluation (T&E) of AI and machine learning models and algorithms to give national security customers insights into the capabilities of applying AI to solve real world problems.

Responsibilities:

• Perform data analysis, test and evaluation of existing machine learning algorithms, and development of advanced algorithms to model physical and autonomous systems,

• Work with MORSE’s current team of engineers to transition algorithms to software applications and real-time embedded systems.

• Support the transition of the developed algorithms to software using one or more programming languages such as Python, C, C++, Java, or MATLAB.

• Work with customers, stakeholders, and other vendors to present concepts, analyses, and test results

• Present a path forward and solutions to solve complex data problems

• Research and identify new methods for machine learning and data analysis

Requirements:

• US CITIZENSHIP REQUIRED and an active Top Secret Security Clearance with SCI eligibility 

• Masters or Ph.D in Data Science, Computer Science, Engineering, Applied Mathematics, Physics, Physical or Biological Sciences or a related field

• 3+ years of experience in Data Science or Analysis

• Solid understanding of data analysis, physics, linear algebra, statistics, algorithms, optimization, and/or machine learning methods

• Proficiency in one or more programming languages like Python, Matlab, C, or C++

• Demonstrated experience with large, multidimensional, or complex data sets in one or more of the following areas: parsing, cleaning, storage strategies, provenance tracking, database formats, and parallelized data transformations

• Good communication skills

• Self-starter and driven

• Prior experience in defense is a plus

MORSE is looking for an Autonomy Software Engineer to research, develop and prototype novel autonomy software to enable pre-mission planning and operation of novel aircraft and other autonomous systems. MORSE is seeking an aeronautical, aerospace, mechanical, or electrical engineer in optimization, estimation theory, and/or guidance, navigation and control (GNC) algorithms. Responsibilities will include autonomy development from conceptualization, including the selection and evaluation of sensors, implementation, including software development, and evaluation, including data analysis. The role will involve developing and testing code in a simulation and HWIL environment as well as field tests of the implemented autonomy software. The ideal candidate will have a strong foundation in physics, math, statistics, and computer science, as well as experience handling electronic hardware and machine learning. The candidate will work with a multidisciplinary team in an agile environment to rapidly design, prototype and test autonomous systems.

Responsibilities:

• Research, develop, and prototype novel autonomy software and algorithms for autonomous systems

• Develop and evaluate autonomy software from conceptualization to implementation, including selection and evaluation of sensors, software development, and data analysis

• Design, develop, and test algorithms for autonomous systems, including sensor fusion, guidance, navigation, and control

• Develop and test code in simulation and Hardware-In-the-Loop (HWIL) environments, as well as participate in field tests of implemented autonomy software on vehicles and systems

• Collaborate with a multidisciplinary team in an agile environment to rapidly design, prototype, and test autonomous systems

Requirements:

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

• The candidate must have experience developing real-world solutions with computational constraints, measurement errors, and modeling uncertainty

• 5+ years of Autonomy, Guidance, Navigation and or Controls experience 

• Experience with developing both algorithms and the simulations for test and validation

• Expertise in positioning, navigation, and timing, particularly for aircraft

• The ideal candidate will have experience working on complex, multi-disciplinary R&D programs

• BS. or M.S. (preferred) in Aeronautical/Aerospace, or Electrical Engineering (Control or Signal Processing focus)  or equivalent degree/major

Desired Qualifications:

• Expertise in sensor fusion such as Kalman filtering and experience with multiple sensing modalities

• Experience with designing and integration of autonomy hardware (sensors, flight controllers)

• Experience with C++ and Python software languages and software design best practices.

• Experience with sensor modeling, simulation, and performance analysis

• Experience in ML model development and deployment using open-source tooling such as PyTorch and ONNX

• Ability to lead a small multi-disciplinary team is a plus

MORSE is seeking a Human Computer Interaction Engineer to conduct user research, design, prototype, and evaluate systems under development. As a Human Computer Interaction Engineer, you will assist in design efforts for novel, cutting edge mobile, web, and software applications in artificial intelligence, machine learning, test & evaluation, and aerospace. You may also do front end software development, Many of the systems we develop are the first of their kind and are highly specialized for the military personnel who use them. We strongly believe that user-centered design is the only methodology to properly develop these systems.

This role will require superior communication and presentation skills. This person will be expected to conduct user research exercises to gain domain knowledge/insights and evaluate prototypes. This person must also be able to convey ideas/concepts to the rest of the development team and to stakeholders. This role requires a design background in some shape or form: either formal training or experience designing applications. Also, the ability to convey ideas visually through sketches, prototypes, or adobe tools is a necessity. Finally, this position requires candidates to have software development skills. Being able to implement designs (in code) is highly desired for this position.

RESPONSIBILITIES:

• Collaborate with cross-functional teams to define and design user experiences for Mobile, Desktop, and Web applications

• Design and development of software applications and software implementation of user interaction/experience designs

• Conduct user research exercises to gain domain knowledge/insights and evaluate prototypes

• Design, prototype, and evaluate novel data visualizations

REQUIREMENTS:

• US Citizenship required and ability to obtain a US Security Clearance.

• BS  degree in Information Design, Human Computer Interaction, Computer Science, Data Science, Engineering, or related subject

• An Interest in User Interface (UI) Design, User Experience (UX Design), Human-Machine Teaming, Human-AI Teaming, Human Computer Interaction, and/or Human Factors

• Experience conducting user research and understanding of various methods to perform such studies

•  Experience with Python, JavaScript, and React 

• Experience designing and prototyping software applications

• Visual design experience

• Exemplary communication skills (move higher) presenting to internal teams

• Self-starter and driven

MORSE is searching for a Lead Data Scientist with expertise in data analysis, data science, and algorithm development in one or more of a variety of fields including visual classification, big data, natural language processing, machine translation, time sequenced data, and advanced metrics. You will lead teams and strategy for Algorithm Test and Evaluation (T&E) of AI and machine learning models and algorithms to give national security customers insights into the capabilities of applying AI to solve real world problems.

Responsibilities:

• Define goals and expectations for algorithm T&E performance

• Research artificial intelligence data splitting, metrics, and T&E methodology

• Lead strategy and coordination with algorithm development vendors

• Work with customers, stakeholders, and other vendors to present concepts, analyses, and test results

• Present a path forward and solutions to solve complex data problems

• Work with MORSE’s current team of engineers and scientists to transition algorithms to software applications and real-time embedded systems.

Requirements:

• US CITIZENSHIP REQUIRED and an Active Top Secret U.S. Security Clearance with SCI eligibility (TS/SCI) 

• Masters or Ph.D in Data Science, Computer Science, Engineering, Applied Mathematics, Physics, Physical or Biological Sciences or a related field

• 7+ years of experience in Data Science, Artificial Intelligence, or Machine Learning

• Expertise in artificial intelligence, machine learning, and data science 

• Experience in algorithm development and testing

• Excellent communication and presentation skills

• Self-starter and driven

• Ability to be onsite 4-5 days/week 

We are seeking a Machine Learning Engineer to join our team at MORSE.  You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer vision (CV) and other types of data. You will be responsible for acquiring truth data, integrating algorithms, testing algorithms, combining algorithms, reviewing literature to stay on top of the latest-and-greatest methods, analyzing data from field tests, and developing advanced algorithms.  MORSE’s AI & ML work crosses modalities, and experience or interest in the fields of Large Language Models (LLM), audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE’s current team of engineers to transition algorithms to production, which may run on on-prem servers, on the cloud, or on a real-time embedded system. You will be part of our team working to accelerate our US National Security customers abilities to use natural language processing capabilities in mission-critical environments. 

Responsibilities: 

• Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.  

• Use MLOps tools for efficient experiment tracking, data management, and reproducibility 

• Write robust, efficient, and maintainable code 

• Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE 

• Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models 

Skills and Requirements: 

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

• Masters or Ph.D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or related field 

• Proven experience in applying CV models, techniques, frameworks, and libraries to implement and fine-tune models 

• Proven experience testing and validating the performance of AI technologies in real-world applications 

• Proficiency in Python  

• Experience with cloud platforms (AWS and Azure)  

• Experience with Docker 

• Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc. 

• Exceptional communication skills and the ability to work well with customers 

• Understanding of Department of Defense requirements and standards is a plus 

We are seeking a Machine Learning Engineer to join our team at MORSE.  You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer vision (CV) and other types of data. You will be responsible for acquiring truth data, integrating algorithms, testing algorithms, combining algorithms, reviewing literature to stay on top of the latest-and-greatest methods, analyzing data from field tests, and developing advanced algorithms.  MORSE’s AI & ML work crosses modalities, and experience or interest in the fields of Large Language Models (LLM), audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE’s current team of engineers to transition algorithms to production, which may run on on-prem servers, on the cloud, or on a real-time embedded system. You will be part of our team working to accelerate our US National Security customers abilities to use natural language processing capabilities in mission-critical environments. 

Responsibilities: 

• Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.  

• Use MLOps tools for efficient experiment tracking, data management, and reproducibility 

• Write robust, efficient, and maintainable code 

• Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE 

• Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models 

Skills and Requirements: 

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

• Masters or Ph.D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or related field 

• Proven experience in applying CV models, techniques, frameworks, and libraries to implement and fine-tune models 

• Proven experience testing and validating the performance of AI technologies in real-world applications 

• Proficiency in Python  

• Experience with cloud platforms (AWS and Azure)  

• Experience with Docker 

• Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc. 

• Exceptional communication skills and the ability to work well with customers 

• Understanding of Department of Defense requirements and standards is a plus 

We are seeking a Machine Learning Engineer to join our team at MORSE.  You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer vision (CV) and other types of data. You will be responsible for acquiring truth data, integrating algorithms, testing algorithms, combining algorithms, reviewing literature to stay on top of the latest-and-greatest methods, analyzing data from field tests, and developing advanced algorithms.  MORSE’s AI & ML work crosses modalities, and experience or interest in the fields of Large Language Models (LLM), audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE’s current team of engineers to transition algorithms to production, which may run on on-prem servers, on the cloud, or on a real-time embedded system. You will be part of our team working to accelerate our US National Security customers abilities to use natural language processing capabilities in mission-critical environments. 

Responsibilities: 

• Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.  

• Use MLOps tools for efficient experiment tracking, data management, and reproducibility 

• Write robust, efficient, and maintainable code 

• Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE 

• Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models 

Skills and Requirements: 

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

• Masters or Ph.D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or related field 

• Proven experience in applying CV models, techniques, frameworks, and libraries to implement and fine-tune models 

• Proven experience testing and validating the performance of AI technologies in real-world applications 

• Proficiency in Python  

• Experience with cloud platforms (AWS and Azure)  

• Experience with Docker 

• Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc. 

• Exceptional communication skills and the ability to work well with customers 

• Understanding of Department of Defense requirements and standards is a plus 

The Opportunity

We are seeking an experienced Associate Director, Contracts to refine and scale our contracting operations and review as we prepare for a potential drug launch. This role will own the full contract lifecycle process—from intake and template selection through, execution and post‑execution management, including negotiating certain agreements independently. This is a highly visible, customer‑service‑oriented role that will serve as the internal subject‑matter expert and trainer for Amylyx’s contract lifecycle management system (CLMS). The ideal candidate will have a strong background in contract management and negotiation within the life sciences, biotech, or pharmaceutical industry and thrive in a fast‑moving, evolving environment.

Responsibilities

Contract Management & Operations

• Optimize and implement contracting processes and best practices, ensuring efficient workflows, compliance, and continuity across teams.
• Manage end-to-end contract lifecycle for a broad set of contracts, e.g. services, confidentiality, research collaborations, and other commercial or operational contracts.
• Maintain the contract management system and repository, including metadata accuracy, key date tracking, renewal management, obligation monitoring, tags, parties and reporting.
• Partner closely with internal stakeholders (Legal, Compliance, Finance, Procurement, Clinical, Commercial, and other business partners) to ensure contract terms align with business and compliance needs.
• Develop, update, and maintain contract templates and playbooks in partnership with Legal advisors.
• Develop and maintain CLMS training materials and provide new hire and refresher training sessions as well as ad hoc support.
• Establish and track contracting KPIs, dashboards, and metrics to provide visibility into system performance and contracting volume.
• Partner with the IT Administrator to drive continuous contracting process improvements, including identifying opportunities to streamline workflows through automation and the use of Artificial Intelligence tools.

Contract Review & Negotiation

• Prepare and negotiate agreements independently or escalate non-standard terms to manager with potential positions.
• Develop and maintain contract templates and playbooks.

Required Qualifications

• Bachelor’s degree required; JD or Paralegal Certification preferred.
• 8+years of experience in contract management and with CLM system(s); experience independently negotiating contracts.
• Strong ability to prioritize, independently manage workload, and meet deadlines in a dynamic environment.
• Exceptional written, verbal, and interpersonal communication skills with a focus on customer service and excellent attention to detail.
• Proven ability to work with cross-functional teams and build strong internal relationships.
• Aligned with a patient‑focused mission and able to uphold the highest standards of integrity.

Preferred Qualifications

• Experience with LinkSquares contract lifecycle management system.
• Demonstrated experience applying AI tools to contract review or process optimization.
• Industry experience in biotech, pharma, or life sciences.

Work Location and Conditions

• At Amylyx, we proudly support remote work opportunities within the United States. However, due to business considerations candidates must be able to attend meetings at our office in Cambridge, MA on a regular basis.  Preference will be given to candidates who reside in the New England region and can be in person on an as needed basis.
• When working remotely, you must have access to a work setting which enables meeting all requirements of the role (including privacy, reliable internet access, phone, ability to video conference, etc.) at your remote location.

Overview of the role:

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

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

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

Location:

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

Responsibilities:

Deep Domain Ownership:

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

Full-Stack Product Execution:

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

The intelligence platform for Science:

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

Cross-Functional Orchestration:

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

Qualifications:

Core Product Experience:

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

The Full-Stack Mindset:

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

Bias for Action in Complexity:

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

Operational Rigor:

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

Preferred Skills:

Scientific Background:

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

Building for Scientists:

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

Startup DNA:

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

Your impact at LILA

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

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

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

Expertise Area 1 — Agentic system building

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

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

Expertise Area 2: Distillation

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

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

Expertise Area 3 — Scalable experience generation

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

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

What you’ll need to succeed:

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

Bonus points for:

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

Scientific rigor & persistence:

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

Your Impact at LILA

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

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

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

Work Streams

Stream A: GPU Optimization & Training Performance

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

Stream B: Stack & Infrastructure

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

Stream C: Model Experimentation

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

Stream D: Evaluations & Benchmarks

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

Stream E: Agentic Capabilities & Frontier Research

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

What You'll Need to Succeed

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

Bonus Points For

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

Location

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

Your Impact at LILA

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

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

What You'll Be Building

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

What You’ll Need to Succeed

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

Bonus Points For

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

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.

What You’ll Do

• Be scrappy to find new sources of audio data and bring it into our ingestion pipeline
• Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.
• Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.
• Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team’s dataset roadmap to power Speechify’s next-generation consumer and enterprise products.

An Ideal Candidate Should Have

• BS/MS/PhD in Computer Science or a related field.
• 5+ years of industry experience in software development.
• Proficiency with bash/Python scripting in Linux environments
• Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)
• Experience with web crawlers, large-scale data processing workflows is a plus
• Ability to handle multiple tasks and adapt to changing priorities.
• Strong communication skills, both written and verbal.

What we offer

• A fast-growing environment where you can help shape the company and product.
• An entrepreneurial-minded team that supports risk, intuition, and hustle.
• A hands-off management approach so you can focus and do your best work.
• An opportunity to make a big impact in a transformative industry.
• Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
• Opportunity to work on a life-changing product that millions of people use.
• Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
• Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.

Compensation: The United States base salary range for this full-time position is $140,000-$200,000 + bonus + equity depending on experience

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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

About Pioneering Intelligence

Pioneering Intelligence builds on Flagship Pioneering's legacy of founding cutting-edge science and computational ventures, harnessing recent advances in AI, machine learning, and data to accelerate fundamental research and create a portfolio of AI-first companies. As part of Flagship's integrated model of science, entrepreneurship, and capital, it transforms breakthrough ideas into world-changing companies, elevating the AI advances happening across the ecosystem in human health, sustainability, and beyond.

The Role

The Pioneering Intelligence team at Flagship Pioneering builds the digital and AI foundation that accelerates the creation and growth of our companies. We are seeking a Vice President of Engineering to lead a medium sized team of Principal Software Engineers, each operating as the technical authority for their own product area.

This is a non-traditional engineering leadership role. Rather than managing a layered organization, you will build and support a team composed entirely of senior individual contributors operating as technical leads at the highest level. Each engineer owns end-to-end technical decisions, builds hands-on, and engages directly with scientific users. Your job is not to manage their work but to set the conditions in which exceptional engineers do their best work, remove obstacles, raise the collective bar, and translate technical strategy into organizational direction.

You remain technically active. You will contribute to architectural decisions, review complex system designs, and stay close enough to the work to lead credibly. You spend roughly 25% of your time in hands-on technical work. The rest is spent on strategy, people, and organizational leadership: building the team, aligning with product leadership, representing the function to senior stakeholders, and driving the conditions for fast, high-quality delivery across the portfolio.

The model is intentionally fluid. Principal Engineers on this team may move between pure IC work and the formal coordination of other resources as project needs evolve, including the management of fully embedded software engineering contractors. It is the VP who balances resources across all teams and projects, in close collaboration with product and strategy leads, ensuring the right people are working on the right things at the right time.

You will work in close partnership with product and strategy leads and alongside a team of peers who expect the same rigor and accountability from you that you expect from them.

Key Responsibilities

• Lead and develop a team of approximately five Principal Software Engineers, each owning technical authority for their own product area
• Set technical strategy and architectural direction for the AI and digital platform, making or ratifying the most consequential build-vs-buy and system design decisions
• Stay technically active: contribute to architectural reviews, design complex systems, and maintain the credibility to lead a team of principal-level engineers
• Build and maintain the team itself: hire exceptional engineers, develop their careers, and create a culture where the floor is principal-level performance
• Represent engineering to product leadership, senior stakeholders, and across the Flagship ecosystem, translating technical direction into business impact
• Balance resources across all teams and projects in close collaboration with product and strategy leads, including decisions about when Principal Engineers take on formal coordination of embedded SWE contractors versus pure IC work
• Drive delivery across the portfolio by removing blockers, resolving cross-team dependencies, and ensuring the team ships with speed and quality
• Model and advance an AI-native engineering culture, including the use of tools like Claude Code as organizational force multipliers

Professional Experience and Qualifications

Experiences

• Has led a team of senior individual contributors or principal-level engineers, ideally in a lean, high-velocity organization where the team was small and the scope was large
• Has served as the technical authority on a complex, production-grade system, not as a manager who delegates the hard parts, but as an engineer who owned them
• Has built and scaled engineering organizations in ambiguous, fast-moving environments, ideally at a startup or within a high-autonomy team inside a larger organization
• Has worked closely with scientific or domain-expert users and understands how to build products that serve researchers, not just operators
• Has hired and developed principal or staff-level engineers, with a track record of raising the technical bar of a team over time

Skills

• Technically credible at the system design level: can evaluate architectural decisions, identify risk in complex designs, and contribute meaningfully to the hardest engineering conversations
• Leads through clarity: sets direction, makes decisions, and communicates tradeoffs without requiring repeated alignment
• Builds teams, not just products: knows how to hire exceptionally, develop senior talent, and create conditions where strong engineers stay and grow
• Fluent in AI-native ways of working and comfortable leading a team that uses tools like Claude Code as a core part of their engineering practice
• Writes with the same precision they expect from their engineers: strategy docs, architectural reviews, and hiring rubrics that don't require a follow-up meeting

Traits

• Strategic and hands-on at the same time: comfortable moving between organizational leadership and technical depth without losing credibility in either
• High standards without bureaucracy: holds the team to an exceptional bar without slowing them down with process for its own sake
• Founder-minded: attracted to ambiguity, motivated by impact, and able to build clarity from uncertainty rather than waiting for it to arrive
• Direct and decisive: makes calls with available information, owns the outcomes, and creates psychological safety for their team to do the same
• Multiplier, not bottleneck: earns trust by making the people around them better, not by centralizing decisions

Why Pioneering Intelligence?

• Lead a team of principal-level engineers where the work is genuinely hard and the people are genuinely exceptional
• Shape the technical strategy of an AI-native platform at the intersection of cutting-edge AI and life sciences
• Operate with the autonomy and organizational support to build the team and culture you believe in
• Work at the frontier of AI-augmented engineering, where the tools are state-of-the-art and the model of how software gets built is being reinvented
• Collaborate with visionary scientists, founders, and builders across Flagship's ecosystem
• Competitive compensation and benefits, including equity, commensurate with experience

About Flagship Pioneering

Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  

Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.

At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact.

We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship.

Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.

The salary range for this role is $313,000 - $400,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Pioneering Intelligence currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Pioneering Intelligence's good faith estimate as of the date of publication and may be modified in the future.

About Acceleron Fusion

Acceleron Fusion is a venture-backed clean energy startup developing breakthrough fusion technology. Founded to commercialize Department of Energy-funded research, we completed our Series A funding round and are working with leading research institutions like the Paul Scherrer Institute and Oak Ridge National Laboratory at the forefront of fusion energy innovation. Headquartered in Cambridge, MA, we are a growing startup of about 20 employees. As a key member of our small and dynamic team, you'll have the opportunity to make a significant impact on our technology and shape the future of both our company and the field of fusion energy.

About this role

We’re looking for a hands-on, scientifically-minded individual to join our team as a Junior/Associate Lab Technician. In this role, you will be instrumental in the fabrication of parts and assembly of components for our cutting-edge muon-catalyzed fusion research apparatus. This position offers a unique opportunity to gain experience across all aspects of our research, including mechanical, electrical, chemical, and vacuum systems. It is ideal for someone passionate about building and excited to contribute to ground-breaking fusion research.

What you’ll do:

• Experimental Assembly & Monitoring: Build and assemble precision components, leak-test vacuum hardware, and assist in monitoring experiments during active runs.
• Fabrication & Machining: Program and operate CNC mills, lathes, and 3D printers to create prototype parts. (We are happy to train the right candidate on advanced CNC workflows).
• Shop Stewardship: Assist in the setup, organization, and safety of our machine shop in Cambridge.
• Field Integration: Travel with the team for several weeks per year to help install, align, and troubleshoot mechanical systems at partner labs in Switzerland, Vancouver, and New York.
• Design Support: Collaborate with scientists and engineers to improve designs for manufacturability.

What we’re looking for:

• Recent graduate with a degree in Physics, Mechanical, Electrical, or Chemical Engineering, or related technical field, or comparable work experience in a technical laboratory or manufacturing environment.
• A “maker” history with a strong portfolio of projects you’ve built or worked on. 
• Familiarity with CAD software, and experience with CNC machining or a strong desire to learn.
• Demonstrated ability to troubleshoot complex systems in a fast-paced, startup environment.
• Strong communication and collaboration skills, able to work effectively within a small, tight-knit team.
• Hands-on experience with low-voltage wiring and control circuits.

Preferred qualifications (not required):

• Experience with Solidworks.
• Hands-on familiarity with vacuum, cryogenic, or pneumatic systems.
• Basic experience with welding (MIG/TIG/Laser).

Details & Logistics:

• This is a full-time, onsite role working from our facility in Cambridge, MA. Preference will be given to candidates already in the Greater Boston area.
• Travel (including international) for several weeks per year is required.
• Our benefits package includes health & dental insurance, retirement savings with company contribution, stock options, paid time off, and 11 company holidays.
• The salary range for this role is $50K to $70K. This range represents the minimum and maximum base compensation Acceleron Fusion reasonably expects to pay for this position. The specific salary offered will be determined based on relevant factors including skills, experience, qualifications, and location. This position may also be eligible for additional compensation such as bonuses, equity, or other benefits.
• Successful applications will include pictures of parts you have made or machines/systems you have built.

#LI-Onsite

Role Summary

Prime Medicine is seeking an AI & Informatics Engineer to join our AI Foundry and support our pipeline delivery.  This includes designing and building the data and computational infrastructure that powers our prime editing programs. This role spans laboratory informatics, NGS pipeline development, and AI-enabled tooling, giving the right candidate a direct line from the work they do to the therapies we develop. You will partner closely with research scientists, computational biologists and technical development professionals, turning raw data into reliable scientific insights, and building automation and AI capabilities that let teams work faster and smarter.

Our ideal candidate brings strong software engineering fundamentals, hands-on NGS pipeline experience, a practical understanding of modern AI frameworks, and the biological intuition to translate scientific needs into working systems. Equally welcome are candidates who entered this space from the life sciences side and have built serious software skills along the way.

This is an action packed and dynamic role where the successful candidate will be involved in multiple programs and activities, so excellent organizational abilities, communications and strong collaboration are critical. The ideal candidate thrives when working in a fast-paced environment, working with purpose, and making an impact for patients.

Key Responsibilities

NGS Pipelines and Data Infrastructure

• Design, develop, and maintain scalable bioinformatics pipelines for NGS data analysis, including amplicon sequencing for on-target editing quantification, using Nextflow and Docker to ensure reproducibility.
• Build and maintain data infrastructure connecting NGS instruments, electronic laboratory notebooks (e.g., Benchling), data repositories, and AWS cloud compute, including automated data ingestion, scalable storage, and provenance tracking.
• Build APIs, MCPs, dashboards, and other internal tools that expose genomic data and analytical capabilities to scientific and cross-functional teams.

Laboratory Informatics

• Support implementation and ongoing development of laboratory informatics systems, including data ingestion from key instruments and integration with laboratory data platforms such as Benchling.
• Support vendor relationships and delivery outcomes for external collaborators, driving requirements, managing implementations, and ensuring high-quality delivery.

AI-Powered Tools and Automation

• Build AI-powered and agentic capabilities that automate routine work, support scientific reasoning, and improve how data and knowledge flow across the organization.
• Develop reusable platform components for retrieval, orchestration, and model interaction, with human-in-the-loop workflows that make AI systems transparent and practical for scientific users.
• Identify and address automation opportunities and scalability bottlenecks across research and operational workflows.

Engineering Practices

• Write production-grade code using Git-based workflows, peer review, testing, CI/CD, and documentation best practices; convert research prototypes into robust, maintainable software.
• Build integrations between internal tooling and third-party platforms to support evolving scientific and operational needs.
• Participate in cross-functional projects spanning lab operations, software engineering, and bioinformatics; recommend best practices, system architectures, and design patterns.
• Perform code reviews and contribute to documentation of engineering and cross-functional practices.

Qualifications

Required

• BS with 5+ years or MS with 3+ years of industry experience in Engineering, Bioinformatics, Data Sciences, or a related field. Candidates with biotech or life sciences with substantial software experience are strongly preferred.
• Strong Python development; proficiency with Nextflow (or comparable workflow tools), Docker, AWS, Linux/Unix, and Git.
• Experience developing and deploying bioinformatic data infrastructure, particularly NGS analysis pipelines.
• Experience implementing or integrating laboratory informatics systems, preferably including Benchling.
• Experience developing and maintaining production-grade APIs and SDKs, and rolling out software tooling across an organization.
• Familiarity with LLM frameworks and practical judgment about where agentic approaches add genuine value.
• Track record of shipping software that scientific or technical users adopt and rely on.

Preferred

• Experience building and deploying AI-powered tools or agentic systems in production or research settings.
• Familiarity with gene editing applications (CRISPR, base editing, or prime editing), including amplicon-seq workflows and tools such as CRISPResso.
• Familiarity with relational databases and data visualization tools (e.g., Plotly Dash, Streamlit, Spotfire).
• Experience in a GxP or regulated software environment (21 CFR Part 11, GAMP 5).
• Experience owning vendor relationships and delivery outcomes for external collaborators in laboratory informatics contexts.

Why This Role

Prime editing is a precise technology, and that precision depends on strong informatics, software, and scientific infrastructure. If you believe that better systems, better automation, and better access to data can translate into safer and more effective therapies, this is the right environment. You will build tools that directly shape how Prime generates, analyzes, and acts on scientific data, while helping lay the foundation for programs to come.

Position Overview:

Join a collaborative, agile and dynamic Clinical Development Operations (CDO) team by leading and contributing to transformative clinical programs for patients in rare diseases and beyond.

In this position, you will be hands-on in day-to-day study execution, working closely with internal study team members, clinical sites, and external CROs and vendors. This position is ideal for someone who thrives in a fast-paced, evolving environment, is comfortable wearing multiple hats, and is eager to learn more about clinical trial management and execution. This is a hybrid role requiring a combination of in-office presence (Watertown, MA) and remote work, with expectations aligned to team and business needs.

Key Responsibilities:

· Support the execution of clinical trials from startup through closeout, ensuring adherence to protocol, timelines, and quality standards

· Assist with site startup activities, including regulatory document collection, IRB/EC submissions, and site readiness/activation

· Support development of study and site-facing materials (e.g., ICFs, recruitment materials, study manuals, CCGs, study tools) and coordinate cross-functional review and approval

· Prepare and maintain meeting minutes, action items, and follow-ups for key study team meetings

· Maintain study documentation (e.g., sponsor TMF oversight and ISF support) to ensure completeness, quality, and inspection readiness

· Oversee CRO/vendor TMF activities, ensuring alignment with sponsor expectations, TMF plans, and filing timelines

· Track study progress, enrollment, IRB/EC submissions and queries, and key operational metrics; proactively identify and escalate risks to timelines or deliverables

· Serve as a primary point of contact for CRAs and sites to address day-to-day operational questions and issues

· Track and monitor key subject visits and study milestones to ensure protocol compliance and data integrity

· Support inspection readiness activities, including TMF reviews, audit support, and resolution of findings

· Support clinical sample management activities, including coordination of central labs, sample logistics, tracking, and issue resolution

· Review clinical data, monitoring reports, and protocol deviations to ensure quality, compliance, and timely issue resolution

· Contribute to SOP development, process improvements, and operational best practices within a growing organization

Qualifications:

· BS/BA/RN Degree in science or a health-related field is preferred

· Minimum 2–4 years of clinical research experience; sponsor experience is strongly preferred.

· Familiarity with clinical trial operations, ICH-GCP, and regulatory requirements

· Experience and understanding of EDC systems, TMF systems, and clinical trial documentation

· Familiarity with clinical data review and data management processes, including Data Monitoring Committees

· Highly organized with strong attention to detail

· Ability to manage multiple priorities with a sense of urgency in a fast-paced environment

· Strong communication and relationship-building skills

· Resourceful, proactive problem-solver with a “do-what-it-takes” mindset

· Comfortable operating in a dynamic environment with evolving processes and priorities

· Self-motivated, collaborative, and able to work both independently and cross-functionally

· Positive, team-oriented attitude with a passion for advancing innovative therapies for patients

· Excitement to contribute to Prime Medicine’s culture!

Prime Medicine is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, protected veteran status, or any other characteristic protected 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 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?

This is a rare opportunity to shape and protect the intellectual foundation of a company redefining what’s possible in drug discovery. As Director, Intellectual Property, you will architect and lead the global IP strategy for Parabilis’ Helicon™ platform and pipeline—helping unlock the full value of therapies targeting proteins long considered “undruggable.”

Reporting to the General Counsel, you will operate at the intersection of cutting-edge science and business strategy, partnering closely with Research, Development, CMC, and Business Development to translate breakthrough innovation into durable competitive advantage.

In this highly visible role, you will not only build and scale world-class IP for the organization but also serve as a key strategic advisor to senior leadership—guiding critical decisions across pipeline advancement, partnerships, and long-term value creation.

Key Responsibilities:

• Develop and execute global patent strategies aligned with corporate, R&D, and business objectives.
• Design layered IP protection strategies covering composition of matter, methods of treatment, platform technologies, computational methods, and manufacturing.
• Lead drafting and prosecution of U.S. and international patent applications.
• Conduct invention mining sessions and proactively identify patentable subject matter.
• Oversee global prosecution strategy and manage outside counsel.
• Lead freedom-to-operate analyses and patent landscape assessments.
• Support due diligence for partnerships, collaborations, and financing transactions.
• Serve as primary IP advisor to Research, Clinical, Regulatory, CMC, and Business Development teams.
• Manage IP budgets and implement scalable portfolio tracking systems.
• Present IP strategy updates to senior leadership and Board as needed.

What you’ll need to be successful:

• Ph.D. in chemistry, biochemistry, molecular biology, structural biology, peptide chemistry, protein engineering, or related discipline strongly preferred.
• Registered U.S. Patent Agent or admitted U.S. Patent Attorney in good standing.
• 5+ years of patent experience in biotechnology, including in-house or law firm experience supporting innovative therapeutic platforms.
• Strong familiarity with peptide therapeutics, intracellular delivery systems, oncology drug discovery, and computational drug discovery technologies.
• Demonstrated success building patent estates for platform biotech companies.
• Deep understanding of U.S. and global patent law relevant to life sciences.
• Excellent scientific writing, claim drafting, and strategic communication skills.
• Demonstrated ability to utilize AI tools for day-to-day work; baseline proficiency is expected, and advanced or innovative use of AI is a strong plus.
• Ability to work hybrid preferred; remote considered.

Core Values

Parabilis Medicines 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 $220,000-$290,000 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 Medicines 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.

30 Acorn Park Drive    |     Cambridge, MA 02140    |    www.parabilismed.com

Your Impact at LILA

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

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

What You'll Be Building

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

Partner-Facing Delivery

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

Process & Scale

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

What You’ll Need to Succeed

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

Bonus Points For

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

Your Impact at LILA

We are seeking a motivated and detail-oriented Associate Engineer to join our high-throughput Research Operations team. In this role, you will focus on materials characterization of materials using spectroscopy and microscopy techniques

You will gain hands-on experience with state-of-the-art automation technologies while contributing directly to projects that drive our company’s growth.

This is an excellent opportunity for candidates excited to learn engineering principles, work with advanced laboratory automation, and develop a strong foundation in scientific operations in a dynamic environment.

What You'll Be Building

• Perform materials characterization techniques including SEMXRF, XRD, Optical Microscopy, Nanoindentation, and Profilometer
• Prepare reagents, solutions/electrolytes , samples, and consumables to ensure seamless continuation of experiments across shifts
• Follow detailed standard operating procedures (SOPs) to ensure accuracy, reproducibility, and throughput
• Monitor workflow performance, troubleshoot common issues, and escalate when necessary to ensure continuity between shifts
• Record, organize, and maintain experimental data with high attention to detail
• Identify opportunities to improve efficiency and streamline processes across shift operations
• Flag unusual features or results for scientist review
• Collaborate with scientists and engineers to support diverse projects across life sciences and physical sciences

What You’ll Need to Succeed

• Bachelor’s degree in Chemistry, Physics, Chemical/Materials Engineering, or a related field (or equivalent laboratory experience)
• Attention to detail and strong organizational skills
• Basic understanding of electron microscopy principles
• Hands-on SEM experience (academic or industry). EDS experience is nice to have.
• Experience with sample preparation techniques: sputter coating

Bonus Points For

• Familiarity with surface characterization techniques methods: XRF, optical microscope, XRF, XRD, nanoindentor, profilometer.
• Experience working in high-throughput production environments with a focus on scalability, efficiency, and accuracy
• Basic engineering skills for troubleshooting characterization tools for microscopes, x rays, and lasers
• Familiarity with automated workflows and techniques to operate and generate custom scripts

Your Impact at LILA

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

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

What You'll Be Building

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

What You’ll Need to Succeed

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

Bonus Points For

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

Your Impact at LILA

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

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

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

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

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

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

What You'll Be Building

Lab Operations Strategy & Operating Model

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

Consumables, Reagents & Supply Chain

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

CMMS & Equipment Asset Management

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

Maintenance Management— Build & Oversight

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

AI Integration & Continuous Improvement

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

Vendor & Logistics Management

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

Team Leadership

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

Blueprint Contribution & Multi-Site Scaling

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

What You’ll Need to Succeed

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

Bonus Points For

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

Your Impact at LILA

What You'll Be Building

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

What You’ll Need to Succeed

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

Bonus Points For

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

Your Impact at LILA

Lila Sciences is looking for a Director of Product, Life Sciences strategic and visionary product leader who will shape the future of our therapeutic research and development capabilities. Reporting to the Vice President, Life Science Product, you will lead the strategy, roadmap, and execution for products and platforms at the intersection of drug discovery, chemical synthesis, and scientific intelligence.

What You'll Be Building

• Drive the strategic direction for turning our AI capabilities toward breakthrough solutions in drug discovery, chemical synthesis, and molecular characterization
• Translate strategic objectives into target product profiles (TPPs) and development campaigns that guide science and engineering teams and enable breakthrough innovations in life sciences
• Lead customer and internal-user discovery, serving as the technical link to external customers and partners in the life sciences
• Identify and shape product opportunities grounded in real-world discovery challenges, partnering closely with collaborators, customers, and strategic partners to ensure relevance and downstream value
• Translate insights into clear product requirements, acceptance criteria, and experiment plans that guide engineering and science teams
• Drive product execution from concept to launch while leading cross-functional teams across science, machine learning, automation, and software engineering
• Manage resource allocations (budget, compute, lab access, people) and decisions against a complex set of priorities (e.g., focus of experiments between AI model training and near-term partnership requests)
• Define clear success metrics and milestones, and clearly communicate progress against them to the company, including executive leadership

What You’ll Need to Succeed

• MS, PhD, or equivalent experience in medicinal chemistry, chemical biology, chemical engineering, biochemistry, or a related field, with a strong grounding in experimental science
• 7+ years in Product Management building new and/or experimental products in drug discovery, molecular profiling, machine learning, or scientific software development
• Deep understanding of drug development processes, molecular and cellular research tools, and wet and dry lab workflows
• Experience with small molecule discovery workflows (e.g., lead optimization, ADMET profiling, synthesis planning) is strongly preferred
• Experience defining and executing target product profiles (TPPs) for new drug products, life sciences research tools, or scientific data platforms
• Experience with managing extremely complex, multidisciplinary projects using project management best practices
• Relentlessly output-focused; driven by impact against our mission and program goals, not by doing tasks, owning decisions, or being in meetings
• Proven ability to influence without authority and lead cross-functional teams effectively
• Highly collaborative and empathetic
• High degree of comfort with ambiguity and able to adapt to changing teams and needs
• Able to create small, achievable units of work from large, complex, and ambiguous goals
• Excellent communication and presentation skills, capable of conveying technical information to any audience

Bonus Points For

• Experience with automated/self-driving labs and experience working with (not necessarily having run) ML approaches relevant to drug discovery and molecular science
• Following the rapid evolution of LLMs and other AI solutions and have thoughts and opinions on how this will impact the future of scientific discovery and product development
• Background in partnering with biopharma or research organizations to define collaborative milestones and workflows

Your Impact at LILA

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

What You'll Be Building

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

What You’ll Need to Succeed

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

Bonus Points For

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

Your Impact at LILA

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

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

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

What You'll Be Building

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

What You’ll Need to Succeed

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

Bonus Points For

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

Your Impact at LILA

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

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

What You'll Be Building

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

What You’ll Need to Succeed

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

Bonus Points For

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

Your Impact at LILA

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

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

What You'll Be Building

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

What You’ll Need to Succeed

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

Bonus Points For

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

Your Impact at LILA

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

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

What You'll Be Building

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

What You’ll Need to Succeed

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

Bonus Points For

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

Your Impact at LILA

As a member of our team in the Physical Sciences division, you will design and build intelligent agent-driven systems that enable AI-accelerated and AI-orchestrated process engineering across a broad range of industrial applications. The core mission of this role is to develop methods by which AI agents can reason about, design, simulate, optimize, and operate complex physical and chemical processes using existing or ML-driven process engineering tools. You will focus on creating agentic infrastructures that allow AI systems to plan and execute multi-step process engineering workflows, ranging from process synthesis and flowsheet generation to steady-state and dynamic simulation, control strategy design, and techno-economic evaluation. Your work will directly shape how Lila’s scientific superintelligence performs closed-loop autonomous process engineering to solve real-world problems.

What You'll Be Building

• Architect and implement agentic frameworks that support end-to-end process engineering workflows, including process setup, simulation, optimization, and analysis.
• Develop AI agents capable of autonomously planning, executing, and iterating on process engineering tasks using existing tools (e.g., steady-state and dynamic simulators, optimizers, and data systems).
• Explore agentic approaches for advanced tasks such as process intensification, control co-design, real-time optimization, and closed-loop learning from operational data.
• Improve robustness, interpretability, and reproducibility of agent-driven process engineering workflows; build internal tooling for debugging, observability, validation, and auditability.
• Work with interdisciplinary teams to apply agentic process engineering to a broad range of industrial applications

What You’ll Need to Succeed

• PhD or equivalent experience in Chemical Engineering, Industrial Engineering, Systems Engineering, or a closely related field.
• Research experience in method development for process engineering, a strong publication record in this area or established industry experience
• Hands-on experience with process simulation and optimization tools (commercial or open-source), including steady-state and dynamic modeling.
• Proficiency in Python and scientific/engineering computing ecosystems
• Experience integrating external engineering tools or simulators into automated workflows via APIs, scripting interfaces, or custom wrappers.
• Familiarity with distributed systems, HPC environments, cloud platforms, or scalable compute infrastructure.

Bonus Points For

• Experience developing or integrating agentic frameworks, autonomous planners, or multi-step tool-using AI systems for engineering or scientific domains.
• Experience building computational pipelines, automation systems, or tool-use frameworks for complex engineering or scientific workflows.
• Experience with digital twins, real-time optimization, or model-predictive control frameworks.
• Background in techno-economic analysis (TEA), life-cycle assessment (LCA), or sustainability-driven process design.
• Contributions to open-source engineering software, ML infrastructure, workflow engines, or agent frameworks.

Your Impact at LILA

We're building a talent-dense, high-agency AI safety team at Lila that will engage all core teams within the organization (science, model training, lab integration, etc.), to prepare for risks from scientific superintelligence. The initial focus of this team will be to build and implement a bespoke safety strategy for Lila, tailored to its specific goals and deployment strategies. This will involve technical safety strategy development, broader ecosystem engagement, as well as developing technical collateral including risk- and capability-focused evaluations and safeguards.

What You'll Be Building

• Design and build capability evaluations to test for scientific risks (both known but especially novel) from cutting edge scientific models integrated with automated physical labs, across biological / physical sciences.
• Coordinate and lead threat modelling exercises with internal and external scientific experts, including monitoring for emerging technologies and use-cases.
• Develop and curate high-quality training and test data for evals and safety systems.
• Evaluate risks from Lila’s capabilities, including through interactions with the wider ecosystem of capabilities (e.g. general-purpose frontier models as well as narrow scientific tools)
• Contributing to broader, high-quality research efforts - as and when needed - for scientific capability evaluation and restriction.
• Contribute to external communications on Lila’s safety efforts.

What You’ll Need to Succeed

• A PhD in either a biological sciences domain (e.g., molecular biology, virology, computational biology or related fields) or a physical sciences domain (materials sciences, physics, chemistry, chemical or nuclear engineering, or related fields), or other related experience.
• Experience in scientific computing, across either biological or physical sciences.
• Familiarity with dual-use research and dissemination concerns, across the relevant safety / regulatory / governance frameworks (e.g. export control frameworks, biological and chemical-related conventions and controls).
• Ability to communicate complex technical concepts and concerns to non-expert audiences effectively.
• Demonstrated ability to lead teams of internal and external collaborators in buildout of Lila’s point-of-view on biological / physical risks
• Demonstrated ability to deal with cross-functional stakeholders (science, AI, product, policy) in a complex environment.

Bonus Points For

• Experience in developing or applying ML to biological or physical sciences
• Experience in building evaluations, or conducting red-teaming exercises, across scientific risks for frontier models / narrow scientific tools.

• This position may be based in any of Lila's offices, including Cambridge (MA), San Francisco (CA), or London (UK).

• For US-based candidates (Cambridge or San Francisco), we expect the base salary for this role to fall between $176,000–$304,000 USD per year, along with bonus potential and generous early equity. The final offer will reflect your unique background, expertise, and impact.
• For UK-based candidates, compensation will be determined separately and will be aligned with local market benchmarks and internal leveling.

Your Impact at LILA

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

What You'll Be Building

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

What You’ll Need to Succeed

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

Bonus Points For

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

Your Impact at LILA

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

What You'll Be Building

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

What You’ll Need to Succeed

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

Bonus Points For

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

Your Impact at LILA

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.