We are looking for a highly skilled technical profile who enjoys building new computational methods and turning them into reliable production tools . You will design, implement, and maintain computational biology methods based on multi-omics data. You will ensure that these methods are deployable on internal and external projects and robust at scale. You will work collaboratively with an interdisciplinary team of computational biologists, AI/ML experts, cell biologists, and oncologists to drive drug discovery in cancer.

This role is ideal for someone with an engineering background and a strong interest in biology, but any candidate who wants to build methods that scientists will use every day in production to advance cancer science is a strong fit.

Key Responsibilities

• In close collaboration with scientists, design and implement novel computational biology methods
• Benchmark, validate, and compare alternative approaches; propose and test new algorithms or tools to improve performance, robustness, and scalability.
• Translate research prototypes into production-ready pipelines with clear versioning and documentation. This will involve implementing and maintaining CI/CD workflows (testing, packaging, deployment, monitoring).
• Collaborate with data engineering teams to run pipelines efficiently in our production environment (e.g. containers, workflow managers, cloud infrastructure).
• Work closely with scientists and project teams to align on standards, architecture, and data models.
• Collaborate with the experimental and data generation teams to understand data characteristics and operational constraints.
• Document methods and pipelines so that non-developers can reliably use them (clear user guides, examples, release notes).

Minimal qualifications

• PhD and/or MSc / Engineering degree in Computer Science, Bioinformatics, Applied Mathematics, or related field.
• Strong interest in biology, oncology, and translational research.
• Experience with data processing for omics (RNA-seq, WES/WGS, etc.). Familiarity with common concepts, terminologies and software currently used in the field
• Strong programming skills in Python, with experience developing complex libraries or pipelines.
• Deep understanding of best software engineering practices.
• Comfortable working in a fast-paced, technical and collaborative team.
• Fluency in English is required.

Preferred qualifications

• Familiarity with AWS cloud infrastructure.
• Demonstrated experience in curation, integration, and management of large-scale datasets.

HR Call (15 minutes call) – An initial discussion to better understand your background, experiences, and motivations.

Technical Interview (45 minutes call) – A deep dive into your technical skills and expertise relevant to the role.

Technical Case (30 minutes presentation + discussion) - A case study or problem-solving exercise to assess your strategic thinking and analytical abilities. If possible this can be done in person.

Engineering Case (45-minutes presentation + discussion) - You will be presenting a piece of work you have previously worked on and which you are proud of. This will be in front of the relevant members of the Orakl Oncology team. If possible this can be done in person.

Founders Interview: As final step of our recruitment process, you will meet the founders of Orakl Oncology in person at our office. This meeting is an opportunity for the founders to assess cultural fit and ensure alignment with our company values.