L

Lila Sciences

AI-powered scientific discovery for medicines

Engineer 1 - Research Operations

Full-Time
$75.6k - $100.8k+ Bonus potential + Early-stage equity
Mid
Bachelor's
Cambridge, MA, USA
In PersonOn-site second shift, 2:00 PM to 10:00 PM.
Biology & BiotechTranslational Research & Bench Biology

About the job

Requirements
  • A bachelor's degree in Biology, Biotechnology, Biochemistry, Molecular Biology, Bioengineering, or a related scientific or engineering field, or an equivalent combination of education and relevant laboratory experience.
  • A minimum of 3 years of relevant co-op and industry laboratory experience.
  • Hands-on laboratory experience performing pipetting, reagent preparation, and aseptic technique within Molecular Biology, Microbiology, Biotechnology, Protein Science, or a related field.
  • Ability to follow standard operating procedures and technical instructions while maintaining accurate, complete, and traceable documentation.
  • Ability to recognize unexpected results or workflow behavior, perform initial troubleshooting, and escalate issues appropriately.
  • Ability to organize work, manage multiple priorities, and execute reliably in a fast-paced, high-throughput laboratory environment.
  • Ability to provide clear status updates and work effectively across teams.
  • Ability to work on-site during the scheduled second shift from 2:00 PM to 10:00 PM.
Responsibilities
  • Execute high-throughput automated and manual laboratory workflows using integrated workcells and liquid-handling platforms such as Hamilton, Lynx, Echo, or similar systems.
  • Prepare, organize, and verify reagents, samples, labware, and consumables required for workflow execution.
  • Follow standard operating procedures, work instructions, and safety requirements to support accurate, reproducible, and timely results.
  • Monitor workflows in real time, identify equipment or process issues, perform first-line troubleshooting and recovery, and escalate complex issues when necessary.
  • Perform routine equipment checks, cleaning, maintenance, and readiness activities to support reliable operation of automated systems.
  • Review quality-control outputs and accurately record experimental, equipment, and process data to maintain data integrity and sample traceability.
  • Provide clear end-of-shift handoffs and partner with scientists, automation engineers, and operational teams to communicate workflow status, open issues, and follow-up actions.
  • Contribute to continuous improvement and cross-training efforts that strengthen workflow efficiency, robustness, scalability, and operational coverage.
Desired Qualifications
  • Experience operating automated liquid handlers or integrated laboratory workcells, such as Hamilton, Lynx, Echo, or similar platforms.
  • Experience working in a high-throughput or production-oriented laboratory environment with an emphasis on quality, efficiency, scalability, and operational continuity.
  • Experience reviewing and interpreting quality-control data generated by automated laboratory workflows.
  • Familiarity with laboratory information management, sample-tracking, or workflow-scheduling systems.
  • Experience troubleshooting laboratory automation, performing routine equipment maintenance, or contributing to process improvements.
  • Experience with protein purification or characterization techniques, such as bead-based purification, CE-SDS, colorimetric assays, or biolayer interferometry.
  • Hands-on experience with cell culture, DNA or RNA workflows, or lipid nanoparticle formulation and handling.

About the company

L

Lila Sciences

View
Website

Lila.ai uses artificial intelligence to speed up scientific discovery, targeting medicines and advanced materials. It ingests large scientific data, literature, and experimental results to let AI uncover patterns, propose hypotheses, and guide research plans. The company differentiates itself by tackling deep scientific problems at scale, combining AI with domain knowledge rather than offering generic tools. Its goal is to help humanity by creating new medicines and materials that address major biological and material challenges through data-driven science.

Company Size

501-1,000

Company Stage

Series A

Total Funding

$550M

Headquarters

Cambridge, Massachusetts

Founded

2024

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Simplify Jobs

Simplify's Take

What believers are saying

  • September 2026 Reuters said Lila raised $115 million, valuing it above $1.3 billion.
  • Lila signed IQHQ's 244,000-square-foot Alewife Park lease in Cambridge.
  • Lila joined DOE Genesis Mission Phase I projects with Caltech, LBNL, Northwestern, Argonne.

What critics are saying

  • Lila still discloses no named paying customers, so revenue remains unproven.
  • The $8.5 billion Series B rumor from June 2026 raises execution expectations brutally.
  • If autonomous labs fail to outperform CROs, Lila becomes an expensive science infrastructure vendor.

What makes Lila Sciences unique

  • Founded 2023, Lila builds autonomous labs linking AI with physical experimentation.
  • Lila combines proprietary experimental data, not internet text, with scientific superintelligence.
  • July 2026 DOE Genesis Mission awards validated Lila's platform with Caltech and Argonne.

Help us improve and share your feedback! Did you find this helpful?

Benefits

  • Flexible Work Hours

Growth & Insights and Company News

Headcount

6 month growth

42%

1 year growth

34%

2 year growth

57%
Africa Business Watch
Aug 21st, 2026
AI integration in Single-Use Technologies reshapes biopharmaceutical manufacturing as global corporate AI investment reaches $252.3 billion.

AI integration in Single-Use Technologies reshapes biopharmaceutical manufacturing as global corporate AI investment reaches $252.3 billion. "AI-enabled bioprocessing can reduce costs and development timelines by 30% to 50% as adoption of intelligent single-use systems expands." Boston, Aug. 21, 2026 (GLOBE NEWSWIRE) - As corporate AI investment surpasses $252 billion globally and biopharmaceutical manufacturers accelerate their adoption of intelligent manufacturing systems, the convergence of artificial intelligence and single-use technologies (SUTs) is emerging as one of the most consequential strategic inflection points in bioprocessing. BCC Research's latest intelligence offering, AI Impact on Single-Use Technologies for Biopharmaceuticals Market - BCC Pulse Report, provides a comprehensive qualitative assessment of how AI is fundamentally restructuring upstream and downstream biomanufacturing operations - and where capital is flowing as a result. Key Findings - Global corporate AI investment reached $252.3 billion in 2024, with private investment surging 44.5% and M&A activity increasing 12.1%, according to the Stanford AI Index Report 2025. The U.S. led all nations with $109.1 billion in private AI investment, compared to China's $9.3 billion. Overall AI investment has grown more than 13-fold since 2014, signaling a sustained structural commitment across sectors including biopharmaceuticals. - Asia-Pacific is rapidly emerging as a global leader in biopharmaceutical innovation, driven by government-led digital transformation initiatives including Singapore's National Precision Medicine Strategy and Thailand 4.0, accelerating AI adoption across R&D, manufacturing, and commercialization - with CDMOs and Global Capability Centers (GCCs) at the forefront. - AI integration in bioprocessing is delivering measurable operational gains, with AI and IoT-enabled solutions reducing costs and development timelines by up to 30% to 50% through optimized upstream and downstream processing. More than 60% of biopharmaceutical manufacturers are already incorporating AI and IoT-enabled solutions for process monitoring and control. - Digital twins, AI-powered single-use bioreactors, and Process Analytical Technology (PAT) integrated with machine learning are redefining real-time quality control - replacing traditional daily sampling with continuous in-line monitoring. AI-enabled single-use chromatography systems are demonstrating deviation rate reductions of 50% or greater, while ML models are optimizing transmembrane pressure and flux rates in single-use filtration to reduce membrane fouling. - Emerging technologies reshaping the sector include autonomous manufacturing systems with AI agents controlling processes in real time, hybrid AI models combining machine learning with mechanistic understanding of fluid dynamics and cell biology, and AI-powered automated labs - so-called "AI science factories" - accelerating process development at scale. - Key players driving adoption include Pfizer, Thermo Fisher Scientific Inc., Sartorius, Roche, Novartis, Sanofi, Eli Lilly, and Accenture, alongside specialized AI bioprocessing innovators such as Basetwo, DataHow, Lemnisca, Lila Sciences, PostEra, Isomorphic Labs, Insilico Medicine, CytoReason, Turbine, and NVIDIA. Strategic Implications The convergence of AI and single-use technologies is being driven by structural forces that extend well beyond individual company strategy. Growing demand for biologics and vaccines requires faster, contamination-free production environments - precisely the conditions that single-use systems are designed to support and that AI is positioned to optimize. The shift toward data-centric manufacturing is critical here: SUTs generate high-resolution process data that, when unlocked by AI-powered analytics and predictive maintenance platforms, create compounding operational advantages across the production lifecycle. Regulatory flexibility in the U.S. is accelerating adoption, with American universities developing 40 AI models in 2024 alone - surpassing China's 15 and Europe's 3. By contrast, the EU AI Act's strict risk-based framework and a documented 20% loss of top EU AI research talent to U.S. institutions are creating meaningful adoption gaps. Data silos, fragmented pharmaceutical data platforms, and low AI penetration in biotech patent applications - still approximately 3.5% in 2020 compared to 17.5% across all sectors - further underscore that this transformation remains early-stage, even as momentum builds rapidly. Investment Considerations For investors, the AI-SUT convergence presents a compelling but differentiated opportunity. Anchor commitments signal strong conviction at the top of the market: Novartis committed $3 billion with Isomorphic Labs, Sanofi committed $1.2 billion with Insilico Medicine, Eli Lilly co-invested $1 billion with NVIDIA on an AI supercomputing and digital twin initiative, and Lila Sciences raised $350 million in a Series A backed by Flagship Pioneering, NVIDIA, and General Catalyst. Earlier-stage opportunities are also active, with Basetwo raising $11.5 million for AI-driven process optimization and Lemnisca securing pre-seed funding for AI-driven fermentation scale-up - consistent with the $0.5 million to $1.5 million pre-seed norms typical of early AI bioprocessing ventures. Key risks include infrastructure and standardization challenges inherent to single-use systems, regulatory headwinds in Europe, and persistent data integration barriers that could constrain AI model performance across fragmented pharmaceutical platforms. About the Report AI Impact on Single-Use Technologies for Biopharmaceuticals Market - BCC Pulse Report provides a qualitative strategic analysis of AI adoption trends, emerging technologies, investment activity, competitive dynamics, and regional adoption patterns across the single-use biopharmaceutical manufacturing landscape. About BCC Research BCC Research provides objective, unbiased measurement and assessment of market opportunities with detailed market research reports. Our experienced industry analysts assess growth trends, identify and evaluate new and changing market opportunities, and provide critical information and innovative decision support tools to help inform the strategic decision-making process. For media inquiries, email [email protected] or visit our media page for access to our market research library. Any data and analysis extracted from this press release must be accompanied by a statement identifying BCC Research LLC as the source and publisher. BCC Research LLC 50 Milk St., Ste. 16, Boston, MA 02109 [email protected] | +1 781-489-7301 www.bccresearch.com Legal Disclaimer: EIN Presswire provides this news content "as is" without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the author above.

Mining Press Releases
Aug 21st, 2026
AI integration in Single-Use Technologies reshapes biopharmaceutical manufacturing as global corporate AI investment reaches $252.3 billion.

AI integration in Single-Use Technologies reshapes biopharmaceutical manufacturing as global corporate AI investment reaches $252.3 billion. "AI-enabled bioprocessing can reduce costs and development timelines by 30% to 50% as adoption of intelligent single-use systems expands." Boston, Aug. 21, 2026 (GLOBE NEWSWIRE) - As corporate AI investment surpasses $252 billion globally and biopharmaceutical manufacturers accelerate their adoption of intelligent manufacturing systems, the convergence of artificial intelligence and single-use technologies (SUTs) is emerging as one of the most consequential strategic inflection points in bioprocessing. BCC Research's latest intelligence offering, AI Impact on Single-Use Technologies for Biopharmaceuticals Market - BCC Pulse Report, provides a comprehensive qualitative assessment of how AI is fundamentally restructuring upstream and downstream biomanufacturing operations - and where capital is flowing as a result. Key Findings - Global corporate AI investment reached $252.3 billion in 2024, with private investment surging 44.5% and M&A activity increasing 12.1%, according to the Stanford AI Index Report 2025. The U.S. led all nations with $109.1 billion in private AI investment, compared to China's $9.3 billion. Overall AI investment has grown more than 13-fold since 2014, signaling a sustained structural commitment across sectors including biopharmaceuticals. - Asia-Pacific is rapidly emerging as a global leader in biopharmaceutical innovation, driven by government-led digital transformation initiatives including Singapore's National Precision Medicine Strategy and Thailand 4.0, accelerating AI adoption across R&D, manufacturing, and commercialization - with CDMOs and Global Capability Centers (GCCs) at the forefront. - AI integration in bioprocessing is delivering measurable operational gains, with AI and IoT-enabled solutions reducing costs and development timelines by up to 30% to 50% through optimized upstream and downstream processing. More than 60% of biopharmaceutical manufacturers are already incorporating AI and IoT-enabled solutions for process monitoring and control. - Digital twins, AI-powered single-use bioreactors, and Process Analytical Technology (PAT) integrated with machine learning are redefining real-time quality control - replacing traditional daily sampling with continuous in-line monitoring. AI-enabled single-use chromatography systems are demonstrating deviation rate reductions of 50% or greater, while ML models are optimizing transmembrane pressure and flux rates in single-use filtration to reduce membrane fouling. - Emerging technologies reshaping the sector include autonomous manufacturing systems with AI agents controlling processes in real time, hybrid AI models combining machine learning with mechanistic understanding of fluid dynamics and cell biology, and AI-powered automated labs - so-called "AI science factories" - accelerating process development at scale. - Key players driving adoption include Pfizer, Thermo Fisher Scientific Inc., Sartorius, Roche, Novartis, Sanofi, Eli Lilly, and Accenture, alongside specialized AI bioprocessing innovators such as Basetwo, DataHow, Lemnisca, Lila Sciences, PostEra, Isomorphic Labs, Insilico Medicine, CytoReason, Turbine, and NVIDIA. Strategic Implications The convergence of AI and single-use technologies is being driven by structural forces that extend well beyond individual company strategy. Growing demand for biologics and vaccines requires faster, contamination-free production environments - precisely the conditions that single-use systems are designed to support and that AI is positioned to optimize. The shift toward data-centric manufacturing is critical here: SUTs generate high-resolution process data that, when unlocked by AI-powered analytics and predictive maintenance platforms, create compounding operational advantages across the production lifecycle. Regulatory flexibility in the U.S. is accelerating adoption, with American universities developing 40 AI models in 2024 alone - surpassing China's 15 and Europe's 3. By contrast, the EU AI Act's strict risk-based framework and a documented 20% loss of top EU AI research talent to U.S. institutions are creating meaningful adoption gaps. Data silos, fragmented pharmaceutical data platforms, and low AI penetration in biotech patent applications - still approximately 3.5% in 2020 compared to 17.5% across all sectors - further underscore that this transformation remains early-stage, even as momentum builds rapidly. Investment Considerations For investors, the AI-SUT convergence presents a compelling but differentiated opportunity. Anchor commitments signal strong conviction at the top of the market: Novartis committed $3 billion with Isomorphic Labs, Sanofi committed $1.2 billion with Insilico Medicine, Eli Lilly co-invested $1 billion with NVIDIA on an AI supercomputing and digital twin initiative, and Lila Sciences raised $350 million in a Series A backed by Flagship Pioneering, NVIDIA, and General Catalyst. Earlier-stage opportunities are also active, with Basetwo raising $11.5 million for AI-driven process optimization and Lemnisca securing pre-seed funding for AI-driven fermentation scale-up - consistent with the $0.5 million to $1.5 million pre-seed norms typical of early AI bioprocessing ventures. Key risks include infrastructure and standardization challenges inherent to single-use systems, regulatory headwinds in Europe, and persistent data integration barriers that could constrain AI model performance across fragmented pharmaceutical platforms. About the Report AI Impact on Single-Use Technologies for Biopharmaceuticals Market - BCC Pulse Report provides a qualitative strategic analysis of AI adoption trends, emerging technologies, investment activity, competitive dynamics, and regional adoption patterns across the single-use biopharmaceutical manufacturing landscape. About BCC Research BCC Research provides objective, unbiased measurement and assessment of market opportunities with detailed market research reports. Our experienced industry analysts assess growth trends, identify and evaluate new and changing market opportunities, and provide critical information and innovative decision support tools to help inform the strategic decision-making process. For media inquiries, email [email protected] or visit our media page for access to our market research library. Any data and analysis extracted from this press release must be accompanied by a statement identifying BCC Research LLC as the source and publisher. BCC Research LLC 50 Milk St., Ste. 16, Boston, MA 02109 [email protected] | +1 781-489-7301 www.bccresearch.com Legal Disclaimer: EIN Presswire provides this news content "as is" without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the author above.

Business Wire
Oct 16th, 2025
IQHQ Partners with Lila Sciences for 244,000 SF Lease at Alewife Park

IQHQ partners with Lila Sciences for 244,000 SF lease at Alewife Park. Accelerating Leasing Activity Supported IQHQ's Recently Closed $310 Million Capital Raise Courtesy of IQHQ CAMBRIDGE, Mass.-(BUSINESS WIRE)-IQHQ, Inc., a premier owner and developer of world-class life science districts, today announced that Lila Sciences, Inc. (Lila), an "AI for Science" company developing the world's first scientific superintelligence platform and fully autonomous laboratories for life and materials sciences, has signed a 244,000 square foot lease at IQHQ's Alewife Park district. The Lila lease and IQHQ's accelerating leasing momentum across its premium quality portfolio fueled IQHQ's recently closed $310 million capital raise. Alewife Park is intentionally designed as a large-scale campus experience with unmatched access to highway and rail transportation, first-class amenities, and state-of-the-art collaborative space on one of Cambridge's most coveted sites. Lila's Alewife Park footprint includes both move-in-ready space in addition to a full new construction laboratory building designed to support Lila's long-term growth needs. "Lila Sciences is redefining what's possible in scientific research, and we're proud to provide the foundation for their next phase of growth," said Tracy Murphy, President of IQHQ. "Alewife Park's scale, design, transportation access, and amenities uniquely position the campus to support transformative companies in one of the country's most dynamic life science ecosystems. We look forward to a long-term partnership with Lila Sciences and to delivering future-ready spaces across our high-quality portfolio." Founded in 2023, Lila Sciences combines AI and human scientific ingenuity to generate new knowledge at a scale, speed, and accuracy previously thought impossible. "We are pleased to work with IQHQ to secure the infrastructure that will support Lila's position at the forefront of Scientific Superintelligence," said Darrell Smith, Sr. Director of Real Estate and Facilities at Lila Sciences. "Alewife Park has a unique combination of qualities suited to Lila's growth needs in addition to the wellbeing of our employees, and we look forward to our long-term presence in West Cambridge." To support Lila and Alewife Park's growing occupancy, IQHQ is accelerating the build-out of best-in-class amenities and local community improvements at the district. Highlights include significant improvements at Jerry's Pond and the MBTA Alewife Station headhouse and plaza, a communal garden in partnership with Green Cambridge, an ecological center managed by Mass Audubon for education and community events, pedestrian and bike paths, the planting of over 650 new trees and campus amenities such as a state-of-the-art fitness center and diverse dining options. About IQHQ IQHQ is Giving Progress a Home(TM), empowering the life science community to thrive and succeed by creating and developing districts that inspire innovation and drive progress and growth. IQHQ's focus is to acquire, develop, and operate sustainable life science districts in the U.S. innovation hubs of San Francisco, San Diego, and Boston. To learn more, visit iqhqreit.com or follow us on LinkedIn or Instagram. About Lila Sciences Lila Sciences is building the world's first scientific superintelligence platform and autonomous labs for life, chemistry, and materials science. With capabilities to apply AI to every aspect of the scientific method, scientists can bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about our mission to build scientific superintelligence to solve humankind's greatest challenges at www.lila.ai.

MobiHealthNews
Oct 16th, 2025
Lila Sciences raises $350M to build scientific superintelligence platform

Lila Sciences raises $350M to build scientific superintelligence platform. Since launching in March, the company has raised $550 million. Lila Sciences, a company developing an AI-enabled scientific superintelligence computer, closed a $350 million Series A round, bringing its total capital raise to $550 million in less than a year. The Series A closed in two parts, with the company garnering $235 million in September, co-led by Braidwell and Collective Global. With the announcement of the Series A closing, the company disclosed the support of NVentures (NVIDIA's venture capital arm), Analog Devices, IQT, Dauntless Ventures, Catalio Capital Management, Pennant Investors, a group of investors from the Peter Diamandis' Abundance Membership and other new stakeholders. Existing investors participated in the Series A, including Flagship Pioneering (where Lila originated), General Catalyst, Alumni Ventures, Modi Ventures, ARK Venture Fund, Altitude Life Science Ventures, Common Metal, Dara Holdings, March Capital, the Mathers Foundation, NGS Super, the State of Michigan Retirement System, a wholly owned subsidiary of Abu Dhabi Investment Authority and other individual investors. Lila Sciences develops an AI-powered scientific superintelligence platform, paired with autonomous labs, that runs the entire scientific method. The company's supercomputer evaluates how various aspects of science, biology, microbiology and more can interact. The technology generates hypotheses, designs experiments and learns from results. The Massachusetts-based company will use the funds to build out its AI Science Factories "to produce more scientific tokens via more instruments under AI control than any company on earth and drive new scaling laws for scientific intelligence." Lila Sciences raised $200 million in seed funding in March of this year. At the time of the company's $235 million round in September, it stated that it would use the funds to expand its workforce and establish new hubs in San Francisco, Boston and London to house and scale its teams and AI Science Factories, "where AI can conduct experiments at scale."

Tech in Asia
Oct 15th, 2025
Nvidia joins $115m round for AI startup Lila Sciences

Nvidia joins $115m round for AI startup Lila Sciences. Lila Sciences has secured US$115 million in funding from investors including Nvidia's venture arm, raising its valuation to over US$1.3 billion. Founded in 2023, the company develops AI models and automated labs for scientific research. This brings its total series A funding to US$350 million and overall capital raised to US$550 million. The company plans to use the funds to build "AI Science Factories," including a new automated lab in Cambridge, Massachusetts, and to open its platform to commercial customers. Lila said its platform has drawn interest from firms in energy, semiconductors, and drug development, focusing on generating proprietary scientific data through experiments rather than internet data. Food for thought. Lila's $1.3 billion-plus valuation rests on unproven traction and outside validation. * Lila claims "thousands of discoveries" across several sciences. It has not shared peer-reviewed publications, patents, or named commercial partnerships that would separate breakthroughs from raw experiments. * The company generates proprietary data in autonomous labs to offset scarce high-quality internet data for AI training. With no disclosed revenue or paying customers and no independent validation, the $1.3 billion-plus valuation leans on investor belief in future upside over present market traction. * Rivals such as CuspAI named Hyundai Motor Group, Kemira, and Meta as partners in its first year 1. The startup focuses on computational materials discovery. Lila has not named commercial partners despite interest from energy, semiconductor, and drug firms, which clouds near-term revenue or platform readiness. Enterprise software and cloud vendors can benefit from Lila opening its platform. * Lila is opening AI Science Factories through enterprise software. Systems integrators and vendors in laboratory information management systems (LIMS) or data infrastructure or cloud orchestration can help early users in energy. Semiconductor teams fit this profile too. * CuspAI and others building materials discovery tools have deals in semiconductors 1. The US Department of Energy published an AI strategy 2. Institutions look ready for tools that link AI, robotics, and lab workflows. * Investors in scientific software and lab automation can back firms that ride the autonomous lab shift. Targets include data standardization, experiment tracking, or AI model deployment that AI Science Factory operators will need regardless of which platform wins. How would you feel if you could no longer use Tech in Asia?