Full-Time

Senior Full Stack Engineer

Web Applications

Posted on 9/16/2025

BenchSci

BenchSci

201-500 employees

AI-powered preclinical R&D evidence platform

No salary listed

Toronto, ON, Canada

Hybrid

Hybrid position.

Category
Software Engineering (1)
Required Skills
Microsoft Azure
FastAPI
Python
React.js
MySQL
Jest
Zustand
SQL
Postgres
TypeScript
AWS
Redis
Next.js
Webpack
Storybook
Google Cloud Platform
Requirements
  • A degree in Computer Science/Engineering or a related field within science
  • High comfort working with a React/Typescript front-end and a Python back-end
  • 4+ years of experience working as a professional full-stack developer
  • Deep expertise in modern state management solutions (e.g., React Query, SWR, Zustand, Redux Toolkit) and the ability to architect scalable data-fetching and caching strategies on the client.
  • Experience working with or contributing to design systems and component libraries (Storybook, Radix, Material UI, shadcn/ui, etc.), with a focus on reusability, accessibility, and performance.
  • Experience delivering and optimizing applications over global CDNs at scale.
  • Proven track record in performance analysis: able to profile, benchmark, and optimize both frontend rendering (React/Next.js) and backend request lifecycles (FastAPI, Python).
  • Deep understanding of web performance metrics (Core Web Vitals, TTFT, TTFB, Lighthouse) and how to optimize them.
  • Experience with dynamic imports, tree-shaking, and code splitting strategies in Next.js / Webpack.
  • Solid understanding of relational databases and SQL (PostgreSQL, MySQL or similar)
  • Experience working with cloud platforms (AWS, GCP, Azure)
  • Excellent communication and collaboration skills
  • Strong problem-solving and analytical skills
  • Experience with Frontend and Backend testing frameworks (Jest, Cypress, PyTest, etc.)
  • Strong familiarity with server-less architectures, including trade-offs around cold starts, cost optimization, and scalability.
  • Strong understanding of the Python and Typescript type systems
  • Deep expertise in modern bundling tools and strategies (Webpack, Vite, Turbopack, or similar).
  • Must have strong experience with asynchronous programming (Python asyncio, FastAPI async endpoints, event loops, non-blocking I/O).
  • Familiarity with caching strategies (edge caching, reverse proxies, Redis, etc.) to improve scalability and latency.
Responsibilities
  • Implement new features and bug fixes as part of a larger cross-functional team of data engineers, product managers, designers, and scientists
  • Work within your immediate team of 4-6 full-stack engineers to do technical investigations, solution designs, code implementation with automated tests, and code reviews
  • Architect and implement sophisticated, stateful client-side workflows and user interfaces using modern state management patterns, ensuring a resilient and maintainable data layer.
  • Architect and implement sophisticated, stateful user interfaces, designing a resilient client-side data layer that seamlessly integrates with our FastAPI backend through well-defined API contracts and efficient state management patterns.
  • Drive the evolution of our overall web architecture, making critical decisions on how our Next.js frontend and FastAPI backend interact. This includes shaping our API strategy, defining data fetching patterns, and structuring our applications to ensure scalability and performance from the database to the browser.
  • Lead or consult the authoring of engineering design proposals following our product roadmap at BenchSci
  • Leverage a deep understanding of the business context and the team’s goals to unlock independent technical decisions in the face of open-ended requirements
  • Proactively identify new opportunities (from both internal and external sources) and advocates for and implements improvements to the current state of projects
  • Adhere to and improve our high standards of highly scalable and maintainable code
  • Help set a high standard for exceptional engineers who are outcome-oriented and improve the team's culture
  • Be given an unmatched opportunity for accelerated growth and learn from a team of world-class engineers
  • Provide troubleshooting analysis and resolution in a timely manner
  • Work on projects involving some of the largest pharmaceutical companies in the world
  • Solve difficult problems and bring new perspectives to the team.
Desired Qualifications
  • Hands-on experience designing hybrid architectures that combine server-less, edge, and traditional compute models to optimize for latency and cost.
  • Ability to conduct load testing and stress testing (Locust, k6, JMeter) to validate scalability goals.
  • Experience building and deploying applications using edge functions (e.g., Vercel Edge, Cloudflare Workers, AWS Lambda@Edge).
  • Experience with multi-tenant SaaS architectures and customer-specific builds or deployments.
  • Experience working with Service-Oriented Architectures (SOA) and microservices at scale.
  • Experience with static site generation (SSG), incremental static regeneration (ISR), or hybrid Next.js rendering patterns.
  • Experience designing theming and customization strategies for multi-tenant SaaS products (supporting customer-specific branding at scale).
  • Familiarity with accessibility standards (WCAG, ARIA) and ensuring they are embedded in the design system.
  • Experience creating and consuming Model Context Protocol (MCP) servers, enabling integration with LLMs, tools, and services.
  • Experience with DevOps practices and tools
  • Ability and willingness to mentor other engineers

BenchSci provides a preclinical research platform called ASCEND that uses artificial intelligence and visual machine learning to map disease biology. The platform works by extracting evidence from published experiments, internal data, and vendor catalogs to help scientists generate hypotheses and identify experimental risks. Unlike traditional databases, BenchSci integrates these diverse data sources into a unified map that guides the entire research planning process across an enterprise. The company's goal is to increase the efficiency and success rate of research and development by helping scientists make better data-driven decisions.

Company Size

201-500

Company Stage

Series D

Total Funding

$161M

Headquarters

Toronto, Canada

Founded

2015

Simplify Jobs

Simplify's Take

What believers are saying

  • Merck renewed two-year ASCEND contract in 2026 for deeper AI workflow integration.
  • Multi-year Mila partnership develops AI for hypothesis generation and assay prediction.
  • Thermo Fisher collaboration enhances preclinical R&D productivity with AI tools.

What critics are saying

  • Insilico Medicine's Pharma.AI erodes market share from Merck and Sanofi in 12-24 months.
  • Recursion Pharmaceuticals maps biology 10x faster, commoditizing BEKG in 6-12 months.
  • OpenAI o1-pro obsoletes neurosymbolic AI as pharma adopts generalist LLMs in 18-24 months.

What makes BenchSci unique

  • ASCEND employs neurosymbolic AI with BEKG for evidence-based disease biology mapping.
  • Platform integrates multi-omics, publications, and internal data for customized insights.
  • Deep biopharma workflow expertise enables multi-hop scientific reasoning like scientists.

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Benefits

Remote-first culture

Equity options

15 days vacation + additional day every year

Unlimited flex time

Comprehensive health & dental benefits

Psychotherapist services

Annual Learning & Development budget

Home office set-up budget

Wellness, lifestyle & productivity spending account

Growth & Insights and Company News

Headcount

6 month growth

-3%

1 year growth

0%

2 year growth

0%
Contract Pharma
Dec 9th, 2025
BenchSci Extends ASCEND Agreement with Merck

BenchSci extends ASCEND agreement with Merck. The renewed agreement supports Merck's efforts to integrate AI more deeply into its scientific workflows. BenchSci, a leading provider of AI software for biopharma research and development, renewed its two-year contract with Merck, known as MSD outside of the United States and Canada. The renewed agreement supports Merck's efforts to integrate AI more deeply into its scientific workflows. With ongoing access to ASCEND, scientists can more easily evaluate evidence and surface insights that inform early development decisions. BenchSci's ASCEND is the first neurosymbolic AI platform built to help biopharma understand disease biology at scale. At its core is the Biological Evidence Knowledge Graph (BEKG) - an experimentally grounded foundation that unifies diverse data sources, including peer-reviewed literature, multi-omics datasets, and clinical trial evidence. By combining the BEKG with advanced foundation models, ASCEND powers AI copilots and co-scientists that deliver rapid, explainable insights and enable faster, more confident research decisions. ASCEND also harmonizes each partner's internal data to create a secure, proprietary, and customized map of disease biology, forming a living, evolving foundation for discovery. "Seeing Merck's teams use ASCEND to unravel disease biology, strengthen hypotheses, and make more evidence-driven decisions underscores the real scientific value AI can deliver. This renewed agreement gives us the opportunity to deepen that impact and continue advancing how complex biological questions are explored in early discovery," said Liran Belenzon, CEO and Co-Founder, BenchSci.

BetaKit
Nov 12th, 2025
BenchSci inks multi-year partnership with Mila to develop AI for drug discovery

BenchSci inks multi-year partnership with Mila to develop AI for drug discovery. Toronto-based BenchSci has teamed up with Montréal's AI research centre Mila to build artificial intelligence (AI) systems that can automatically create new scientific hypotheses and forecast the outcome of drug-related tests before they are conducted. BenchSci and Mila say this work could mark "a major step" on the path to autonomous drug discovery. Together, the two organizations hope to develop AI models capable of biological inference, or the ability to generate hypotheses and predictions for the outcomes of experiments during the drug discovery process. They are also targeting experimental assay prediction - which they say would mark "a major step" on the path to autonomous drug discovery. Experimental assay prediction forecasts the outcome of drug-related tests before they are conducted. BenchSci, which sells AI-powered software for biopharmaceutical research and development (R&D), says it has struck a multi-year partnership with Mila to "push the boundaries of predictive and generative modeling in drug discovery." In a statement, BenchSci co-founder and CEO Liran Belenzon argued that this could lay "the groundwork for autonomous labs that accelerate innovation, uncover insights beyond human reach, and bring life-saving medicines to patients faster." BenchSci will gain access to Government of Canada-backed Mila's network of AI experts, which will work alongside the company's team of machine learning scientists. Their combined research will help BenchSci evolve its generative AI R&D platform with new inference models that build on its existing map of disease biology. "By joining forces with BenchSci, we're applying world-class AI research to one of the most complex and impactful challenges of our time - understanding biology at a level that can transform how life-saving medicines are discovered and developed," Mila executive vice-president Stéphane Létourneau said in a statement. Founded in 2015, BenchSci aims to use AI to better understand disease biology for drug discovery. Its software acts as an AI R&D assistant for preclinical organizations. BenchSci says it caters to 16 of the top 20 pharma firms - from AbbVie to Gilead Sciences, Merck, Novartis, Novo Nordisk, and Sanofi - and more than 4,500 research centres globally. BenchSci has raised $218 million to fuel its efforts from a group of investors that includes Al Gore's Generation Investment Management, Inovia Capital, TCV, F-Prime, Gradient Ventures (Google's AI fund), and Golden Ventures. This Mila collaboration follows recent partnerships BenchSci secured with pharma giants Sanofi and Thermo Fisher Scientific. Generative AI has also impacted BenchSci's internal operations. As Belenzon wrote in a blog post this July, BenchSci shifted to an "AI-first" strategy in 2025. Similar to Canadian tech peers like Shopify and Klue, Belenzon wrote that BenchSci is now asking whether or not AI can do a job before it hires new employees. Since BenchSci's $95-million Series D in mid-2023, the company has cut down the size of its team, shedding 70 employees (then 17 percent of staff) in early 2024. It cut another 83 employees (23 percent of its overall workforce at the time) in 2025 in layoffs that were first reported by The Globe and Mail, since confirmed by BetaKit, as the company has adopted AI to slash costs. LinkedIn Insights indicates that BenchSci's headcount has fallen 35 percent over the past two years, to 292 today. This year, BenchSci has also made some changes to its leadership team. The company announced John Jackson as CTO and Peter Grandsard as fractional senior vice-president of strategy, while COO Eran Ben-Ari and director of product Nim Fox have left.

SynBioBeta
Oct 2nd, 2025
BenchSci Partners with Thermo Fisher to Enhance R&D Productivity with AI Tools

BenchSci and Thermo Fisher Scientific have joined forces to develop AI-driven research tools aimed at improving the efficiency of scientific research and drug discovery.

BiopharmaTrend
Sep 30th, 2025
BenchSci and Thermo Fisher Collaborate to Develop AI Tools for Preclinical R&D

BenchSci and thermo fisher collaborate to develop AI tools for preclinical R&D.

Samfiru Tumarkin LLP
Jan 12th, 2024
BenchSci: Severance Packages

January 2024: BenchSci has eliminated 17 per cent of its workforce, or 70 jobs, as it furthers its investment into generative AI.

INACTIVE