Senior Research Engineer - Multimodal Representation Learning

About Valence Labs
Valence Labs is an AI research and productization engine within Recursion dedicated to industrializing scientific discovery to radically improve lives. Combining the intellectual freedom of academia with the resources and stability of industry, our focus is the development of highly-autonomous systems that will spearhead a fundamental shift in the way treatments are discovered and developed for complex disease. Our research is driven by optimism, purpose, and a shared vision for a healthier tomorrow. We publish in top journals and conferences, are deeply committed to open-science and open-source, and maintain some of the largest and most active research communities in our industry. Our team is located in London and Montreal, where we share close connections with Mila, the world’s largest deep learning research institute.
About the role
We’re seeking an experienced Research Engineer to shape and lead the development of software and AI systems that will help in our mission of industrializing scientific discovery to radically improve lives. We're looking for individuals with strong engineering skills, including expertise in designing, implementing, improving, and deploying distributed machine learning systems at significant scale. In addition, we highly value proficiency with state-of-the-art machine learning algorithms and exceptional problem solving skills. In this role, you will:
Support Valence Labs’ research agenda across ML for drug discovery.
Engage with and contribute to open-source libraries developed by Valence and the research community.
Create and improve novel ML methods that will accelerate drug discovery.
Collaborate with an interdisciplinary team of dry and wet lab scientists to inform and improve our models and systems.
Present and communicate research findings through talks, blog posts, publications, and conferences.
A successful candidate will have most of the following:
PhD or Master's degree with 3+ years of industry experience.
Strong programming skills and understanding of modern software development practices, especially in Python.
Scientific knowledge of biology, chemistry, or physics along with previous experience working in a scientific environment across disciplines.
Experience with real world natural science data and the associated challenges.
Experience with high throughput bioassay data such as next-generation sequencing data, cellular imaging data, proteomics data or similar.
Proven track record in machine learning, including multimodal learning, designing new architectures, hands-on experimentation, analysis, visualization, and model deployment.
Demonstrated capability to understand and summarize scientific content and implement deep learning models based on descriptions from publications.
Strong knowledge of linear algebra, calculus, and statistics.
Passion for applying ML research to real-world problems.
Nice to have:
Experience in building and deploying high-performance implementations of deep learning algorithms.
Authorship of publications in peer-reviewed conferences (e.g., NeurIPS, ICML, or ICLR) or journals (e.g. Nature, Science, JACS, or ACS)
Contribution to high-visibility ML codebases.
Valence Labs is committed to creating a diverse and inclusive environment, where understanding and accommodating personal needs and preferences is a priority. Join our multidisciplinary team of passionate researchers, eager to push the boundaries of ML research and contribute to industrializing scientific discovery to radically improve lives.#LI-EP1
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