Software Engineer, BenchSci
Data - Query Intelligence & Infrastructure - 6 Month Contract
AI for biomedical research
Be an early applicant
AI for biomedical research
201-500 employees
Be an early applicant
201-500 employees
Company mission
To exponentially increase the speed and quality of life-saving research by empowering scientists with the world's most advanced biomedical artificial intelligence.
Role
Who you are
- PhD or advanced degree in Computer Science, Software Engineering, or a related field
- A strong background in machine learning, NLP, query analysis, and data science applications
- Experience with graph technologies, including graph databases (e.g., Neo4j, Neptune) and/or graph processing frameworks (e.g., NetworkX)
- Experience designing or working with systems that manage state or context for GenAI models; direct experience with a Model Context Protocol is a significant plus
- Hands-on experience in Python
- Proficiency in query languages (e.g., SQL, Cypher, Gremlin) and optimizing queries over large, complex datasets
- Experience building or supporting ETL pipelines, APIs, or real-time/batch query systems
- Familiarity with cloud environments (GCP preferred), CI/CD pipelines, Docker, and GitHub Actions
- A strong understanding of performance optimization
- The ability to clearly communicate technical concepts to both technical and non-technical audiences
- A collaborative mindset and a growth mindset, staying up to date with advances in ML, graph systems, and data engineering
What the job involves
- We are looking for a Software Engineer, Data to be at the heart of designing systems that understand user intent by leveraging knowledge graphs and Model Context Protocol to deliver Generative AI products
- Your work will involve API development, performance optimization, and maintaining high-performance access to large, interconnected datasets
- In this role, you'll blend machine learning and data engineering expertise to build scalable systems, improve query efficiency, and contribute to production-grade solutions that are deeply context-aware
- Design, implement, and own the Model Context Protocol, ensuring our GenAI systems receive rich, stateful information for advanced query interpretation
- Build and leverage knowledge graphs to model complex data relationships, enhancing the depth and accuracy of our query understanding capabilities
- Develop and maintain robust data pipelines that populate our graph databases and support efficient, real-time query analysis
- Develop and refine APIs that provide fast, reliable access to processed data and insights derived from our graphs and ML models
- Establish, monitor, and improve query performance benchmarks against large-scale graph and tabular datasets
- Contribute to query interpretation and NLP-driven analysis, applying ML techniques to improve system intelligence
- Design and implement scalable, testable solutions using modern frameworks and tools
- Collaborate with colleagues on the design and delivery of data-intensive ML systems that are fundamentally graph and context aware
- Share knowledge and learn from others to continuously raise the technical bar
Salary benchmarks
Our take
Over the past decade, the cost of bringing a drug to market has increased exponentially. But the number of drugs approved has stayed stagnant, leading to a decline in research productivity. Through development of AI-assisted software, BenchSci has allowed scientists to rapidly compute data from scientific journals and product catalogues to dramatically reduce these inefficiencies in the R&D process.
The company offers a lateral solution to traditional, manual data analysis to allow for data leveraging. Plus an automated, comprehensive overview of existing relevant research. These methods have made BenchSci a forerunner in the drug development industry; the company's software is used by leading pharmaceutical companies.
BenchSci continues to invest in its machine learning technology, and in 2023 launched ASCEND. This is software that extracts experimental evidence from internal and external sources to help improve the hit rate of drug trials. It has also raised considerable funds, the latest of which is supporting the expansion of the platform.
Steph
Company Specialist at Welcome to the Jungle
Insights
31% employee growth in 12 months
Company
Funding (last 2 of 7 rounds)
May 2023
$68.8m
SERIES D
Jan 2022
$45.6m
SERIES C
Total funding: $159.5m
Company benefits
- An engaging remote-first culture that hires the best talent from around the world
- Compensation package that includes BenchSci equity options
- Comprehensive health and dental benefits with an emphasis on mental health
- An annual Executive Health Assessment at Medcan for proactive health awareness
- Three weeks of vacation plus an additional day for every completed year
- A $2000 Annual Learning & Development budget
- Generous parental leave benefits with a top-up plan or paid time off options
- Additional time-off: 2 weeks for Winter Holiday, every other Friday in July and August, your birthday, and more!
- A $1000 work from home allowance to make your home setup perfect for you
- An Oculus Quest 2 to connect with your team members in Virtual Reality
- An executive coach for managers to assist in leading high-performing teams
- Complimentary Headspace account to support mental wellness and focus
- Complimentary genome sequencing from 23andMe to better understand your health through your DNA
Company HQ
South Core, Toronto, ON
Leadership
Dr. Elvis Wianda
(Co-Founder & Chief Data Officer)Obtained a PhD studying Health & Medical Physics at the University of Toronto before joining BenchSci.
Dr. Tom Leung
(Co-Founder & CSO)Previously held roles within the University of Toronto as a Research Assistant and Postdoctoral Fellow.
Liran Belenzon
(Co-Founder & CEO)Previously co-founded and held role as CEO at companies including Standy and Biz-Coupon. Currently a CDL Associate at Creative Destruction Lab.
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