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Careers at Biographica

🌽 Safeguarding the future of food<br><br>We’re on a mission to accelerate the development of more productive, sustainable, nutritious & climate-resilient food sources. 

How? By building the world’s first ML-driven target discovery platform for crop gene-editing. <br><br>🧬 From drug target discovery to crop target discovery<br><br>While gene-editing of crops is becoming ever more efficient, identifying which genes to edit and how remains a significant challenge. 

To overcome this bottleneck, we use cutting-edge deep learning to accurately and efficiently identify high value genetic targets for crop gene-editing. 

Our approach draws inspiration from recent advancements in the drug discovery space, incorporating LLMs, transformers and graph-based technologies to build a best-in-class discovery platform for plant sciences.<br><br>

About Us

Cecy studied Biological Sciences at Oxford University and has an MSc in ML from Imperial College London, specialising in graph-based biological modelling. At Biographica, Cecy leads strategy and business development, leveraging prior experience in drug manufacturing and supply chain at GSK as well as market access strategy consulting for gene-editing technologies.

Cecily Price

Dom has Masters degrees in Maths and Stem Cell Biology, as well as a PhD in Computational Genomics, from Cambridge. In his PhD, and later as an ML researcher at Relation Therapeutics, Dom applied graph ML to target discovery. He leads platform development at Biographica, drawing inspiration from drug discovery to design efficient target discovery methods for crop gene-editing.

Dominic Hall

Meet the Founders

Gallery

<html><head></head><body><h2><span style="font-family: helvetica;">About us</span></h2>
<h3><span style="font-family: helvetica;">🌽 Safeguarding the future of food</span></h3>
<p><span style="font-family: helvetica;">Biographica is on a mission to accelerate the development of more productive, sustainable, nutritious &amp; climate-resilient food sources. To achieve this, we're building the world’s first ML-driven target discovery platform for crop gene-editing.</span></p>
<h3><br><span style="font-family: helvetica;">🧬 From drug target discovery to crop target discovery</span></h3>
<p><span style="font-family: helvetica;">While gene-editing of crops is becoming ever more efficient, identifying which genes to edit and how remains a significant challenge. To overcome this bottleneck, we use cutting-edge deep learning to accurately and efficiently identify high value genetic targets for crop gene-editing. Our approach draws inspiration from recent advancements in the drug discovery space, incorporating LLMs, transformers and graph-based technologies to build a best-in-class discovery platform for plant sciences.</span></p>
<h3><br><span style="font-family: helvetica;">👥 Team</span></h3>
<p><span style="font-family: helvetica;">Led by co-founders Dom (CTO) and Cecy (CEO), we are now a team of 12, including 2 ML engineers, 2 data engineers, 3 bioinformaticians. We also have a remote, part-time intern conducting ML research. We primarily work together in person from our office in Spitalfields, London, 4 days per week.</span></p>
<div>&nbsp;</div>
<h2><span style="font-family: helvetica;">What we're looking for</span></h2>
<div><span style="font-family: helvetica;">As our first dedicated software engineering hire, you will play a pivotal role in ensuring that our scientists, ML engineers, and data engineers can work efficiently and at scale. You will take ownership of our target identification software tool, ensuring it is fully tested, scalable and seamlessly connected with other elements of our platform. To do this you will work closely with the science and data teams to ensure that the tool is maximally useful for answering scientific questions and maximally flexible and modular to accommodate future improvements. Additionally, there is potential to explore novel technologies, such as agentic LLMs, to enhance multiple internal scientific tools being developed at Biographica.&nbsp;</span></div>
<div>&nbsp;</div>
<div><span style="font-family: helvetica;"><strong>Important note: </strong>We are looking for candidates with experience in biology even if it isn’t in a research capacity. This job will involve continual work at the interface of software and biology so it’s important that any candidate has background knowledge, the desire to learn more about the intricacies of the subject and the willingness to integrate biological considerations into their software decision making.&nbsp;</span></div>
<div>&nbsp;</div>
<h3><span style="font-family: helvetica;">Responsibilities</span></h3>
<h4><span style="font-family: helvetica;">Core</span></h4>
<ul>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Lead the software development of our target identification tool, ensuring it is robustly tested, scalable, and well-integrated with the broader platform.</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Work closely with science, ML, and data engineering teams to understand their product needs and translate these into functional software.</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Architect the tool with modularity and future enhancements in mind, ensuring it can handle evolving scientific and computational requirements.</span></li>
</ul>
<h4><span style="font-family: helvetica;">Additional</span></h4>
<ul>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Evaluate and potentially integrate emerging technologies, such as agentic LLMs, to enhance internal tools and workflows.</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Develop integrations with other internal tools, with a particularfocus on seamless flow of data.</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Identify opportunities for process and tech improvements that benefit the wider scientific team.</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Collaborate on ad-hoc projects and support various engineering efforts as needed.</span></li>
</ul>
<div>&nbsp;</div>
<h3><span style="font-family: helvetica;">Competencies</span></h3>
<h4><span style="font-family: helvetica;">Core</span></h4>
<ul>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Strong proficiency in Python and a deep understanding of backend development principles.</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Exposure to and experience using at least one application development framework, with an emphasis on creating internal tools rather than consumer-facing products.</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Some experience or familiarity with biology, even if not in a research capacity, and a willingness to learn more about the field.</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Excellent communication skills and a proven ability to work effectively across diverse technical teams.</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">A pragmatic approach to troubleshooting and resolving technical challenges in a fast-paced environment.</span></li>
</ul>
<h4><span style="font-family: helvetica;">Nice to have</span></h4>
<ul>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Experience with AWS services and familiarity with Kubernetes environments (GCP exposure is a plus).</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Interest in emerging technologies and a proactive attitude toward exploring tools like agentic LLMs.</span></li>
</ul>
<div>&nbsp;</div>
<h3><span style="font-family: helvetica;">Benefits</span></h3>
<ul>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Competitive salary &amp; equity options</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">25 days annual leave &amp; option for 2 weeks work from anywhere policy</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Benefits package</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Career development opportunities as the company scales</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Ownership of ambitious, mission-driven work with real-world impact</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Vibrant, innovative &amp; supportive work environment with a committed team</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Access to conferences, events &amp; professional development resources</span></li>
</ul></body></html>

Platform Software Engineer

<html><head></head><body><div><span style="font-family: helvetica;">​At Biographica, we're always on the lookout for passionate and talented individuals who resonate with our mission and values. While we may not have a specific role that matches your profile at this moment, we welcome you to submit a speculative application. By joining our talent pool, you'll be among the first to be considered when new opportunities arise that align with your skills and aspirations.​</span></div>
<div>&nbsp;</div>
<div><span style="font-family: helvetica;"><strong>How it works&nbsp;</strong></span></div>
<div><span style="font-family: helvetica;">Submit your CV and a note detailing your areas of interest and expertise. Our team will review your application and keep it on file. As soon as a relevant position becomes available, we'll reach out to you to discuss potential opportunities.​</span></div></body></html>

Open Application

<html><head></head><body><div>
<div>
<h2><span style="font-family: helvetica;">About us</span></h2>
<h3><span style="font-family: helvetica;">🌽 Safeguarding the future of food</span></h3>
<div><span style="font-family: helvetica;">Biographica is on a mission to accelerate the development of more productive, sustainable, nutritious &amp; climate-resilient food sources. </span><span style="font-family: helvetica;">To achieve this, we're building the world’s first ML-driven target discovery platform for crop gene-editing.</span></div>
<h3><span style="font-family: helvetica;">🧬 From drug target discovery to crop target discovery</span></h3>
<div><span style="font-family: helvetica;">While gene-editing of crops is becoming ever more efficient, identifying which genes to edit and how remains a significant challenge. </span><span style="font-family: helvetica;">To overcome this bottleneck, we use cutting-edge deep learning to accurately and efficiently identify high value genetic targets for crop gene-editing. </span><span style="font-family: helvetica;">Our approach draws inspiration from recent advancements in the drug discovery space, incorporating LLMs, transformers and graph-based technologies to build a best-in-class discovery platform for plant sciences.</span></div>
<h3><span style="font-family: helvetica;">👥 Team</span></h3>
<div><span style="font-family: helvetica;">Led by co-founders Dom (CTO) and Cecy (CEO), we are now a team of 12, including 2 ML engineers, 2 data engineers, 3 bioinformaticians. We also have a remote, part-time intern conducting ML research. We primarily work together in person from our office in Spitalfields, London, 4 days per week.</span></div>
<div>&nbsp;</div>
<h2><span style="font-family: helvetica;">What we're looking for&nbsp;</span></h2>
</div>
<div><span style="font-family: helvetica;">Working within our core ML team (<a href="https://www.linkedin.com/in/paride-antinucci/">Paride Antinucci</a>, <a href="https://www.linkedin.com/in/cobbles/">Jacob Moss</a>) you’ll be helping us build best-in-class genomic foundation models tailored to the plant sciences. This could involve everything from model training to data curation to evals but we welcome applicants with specific expertise who feel they could uniquely contribute to a specific element of the training lifecycle of large complex models.</span></div>
<div>&nbsp;</div>
<div><span style="font-family: helvetica;">The applicant should have explicit experience making use of genomic data in a machine learning context. We are particularly interested in applicants with experience working with foundational generative models of DNA or transcriptomic data. However, our modelling efforts have a strong focus on multi-modality so any experience with or interest in other data modalities (e.g. text) is a plus.</span></div>
<div>&nbsp;</div>
<h3><span style="font-family: helvetica;"><strong>Responsibilities</strong></span></h3>
<h4><span style="font-family: helvetica;">Core</span></h4>
<ul>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Contribution to the development of Biographica’s core proprietary -omics models including model training &amp; eval development.</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Recreation of SOTA models from the scientific literature &amp; benchmarking against Biographica internal models &amp; evals.</span></li>
</ul>
<h4><span style="font-family: helvetica;"><strong>Additional / Development Areas</strong></span></h4>
<ul>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Model deployment ensuring flexible &amp; scalable inference access to our wider Data Science team.</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Collaboration with our bioinformatics team to ingest, standardise and QC data from multiple sources (internal &amp; external) to prepare it for ingestion into Biographica training pipelines.</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Supporting our wider ML team on additional model development and commercial projects.</span></li>
</ul>
<div>&nbsp;</div>
<h3><span style="font-family: helvetica;">Competencies</span></h3>
<h4><span style="font-family: helvetica;">Core</span></h4>
<ul>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Postgraduate experience (MSc or PhD) studying ML with demonstrable application to a biological domain.</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Demonstrable experience building modern architectures (transformers, diffusers, etc.) from scratch and applying them to real biological datasets</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Experience working with large-scale transcriptomic atlases, preferably with experience in non-human organisms (although this is not a requirement)</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Experience working with PyTorch, huggingface transformers &amp; diffusers</span></li>
</ul>
<h4><span style="font-family: helvetica;">Nice-to-have</span></h4>
<ul>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Relevant publications in reputable journals/venues or contributions to open-source projects</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Demonstrable exposure to and interest in probabilistic ML, causal ML or active learning</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Experience with distributed model training (data and model parallelism)</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Experience work on biological data curation, with exposure to data cleansing &amp; pre-processing problems with -omics datasets.</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Exposure to cloud based ML orchestration frameworks such as Sagemaker and Vertex AI.</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Model deployment in an enterprise setting.</span></li>
</ul>
<p>&nbsp;</p>
<h3><span style="font-family: helvetica;">Benefits</span></h3>
<ul>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Competitive salary &amp; equity options</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">25 days annual leave + 8 bank holidays &amp; 2 weeks 'work from anywhere' policy</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Benefits package</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Career development opportunities as the company scales</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Ownership of ambitious, mission-driven work with real-world impact</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Vibrant, innovative &amp; supportive work environment with a committed team</span></li>
<li style="font-family: helvetica;"><span style="font-family: helvetica;">Access to conferences, events &amp; professional development resources</span></li>
</ul>
</div></body></html>

Job Openings

Platform Software Engineer

Open Application

ML engineer (genomics)