At a Glance
- Tasks: Curate and harmonise complex research data using AI to drive scientific discovery.
- Company: Join Altos Labs, a leader in cell rejuvenation and scientific innovation.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Why this job: Make a real impact on health through cutting-edge data engineering and collaboration.
- Qualifications: PhD or equivalent experience in data curation or related fields required.
- Other info: Dynamic team environment focused on diversity and belonging.
The predicted salary is between 36000 - 60000 ÂŁ per year.
Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life.
Diversity at Altos
We believe that diverse perspectives are foundational to scientific innovation and inquiry. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. We are all accountable for sustaining a diverse and inclusive environment.
What You Will Contribute To Altos
Use AI agents to make complex research data FAIR—Findable, Accessible, Interoperable, Reusable—so scientists and product teams can ask richer questions, move faster, and advance discovery. Be part of a team using knowledge and data engineering to enable the transition from manual to LLM‑enabled, agentic data ingestion and curation. You’ll sit at the intersection of data curation, data and knowledge engineering. Your job is to automate the ingestion and standardization of multi‑source datasets into governed, searchable, analytics-ready assets, and to model the domain knowledge that ties them together.
Responsibilities
- Curate and harmonize data. Ingest, profile, clean, normalize, and annotate multi‑modal research datasets (e.g., genomics/transcriptomics, proteomics, imaging/microscopy, CRISPR screens, assay/instrument metadata). Map to controlled vocabularies and standards; manage identifiers, synonyms, and crosswalks.
- Deliver insights from curated data. Focus on the substance—entities, relationships, and annotations that answer real research and product questions using public domain assets from Ensembl, GEO, PubMed, OMIM, OLS, amongst others. Use pipelines and existing data sources storage pragmatically as tools to deliver content and outcomes.
- Model knowledge to serve decisions. Capture the concepts and links researchers actually use; keep schemas lightweight and purpose‑built. Leverage OBO Foundry ontologies; define with LinkML; align to the BioLink/Biolink Model; and integrate/serve with platforms such as BioCypher.
- Quality, governance & AI enablement. Instrument automated checks (tests/expectations), process development to improvement data FAIRification, and LLM‑assisted validations; capture provenance/lineage; codify SOPs; and work to facilitate the migration of processes from manual → automation → agentic (MCP‑integrated) workflows.
- Serve as a key technical liaison between scientific, data science, and engineering teams, translating complex research needs into scalable and maintainable data solutions.
- Define and evangelize best practices for data and knowledge engineering across the organization, mentoring junior team members and building reusable, AI-enhanced, enterprise‑level components.
Who You Are
Minimum Qualifications
- PhD, Biological Sciences, Computer Science, Software Engineering, or related quantitative field, or equivalent technical experience
- Candidates should have relevant experience in data curation, ontology/knowledge engineering, or data engineering (or equivalent experience) at a biotechnology company.
- Mindset: You prioritize data and business objectives over tools; technology is a means to an end.
- Demonstrably strong Python expertise, particularly in the context of data modeling and processing, with strong skills in both relational (SQL) and graph data stores, and the ability to choose pragmatically between them (e.g., Postgres/Redshift vs. Neo4j/Neptune).
- Comfortable building pragmatic ETL/ELT workflows in a major cloud (preferably AWS), using orchestration frameworks or AWS-native tools.
- Active user of AI coding editors such as Cursor, with an active interest in designing and building Model Context Protocol (MCP) applications; motivated to migrate processes from manual → automation → agentic.
- Mature understanding of data quality, provenance, versioning, and “curation as code,” including hands-on use of testing/validation frameworks.
Preferred Qualifications
- Experience in basic/exploratory life‑science research across multiple modalities (genomics/transcriptomics, proteomics, imaging/microscopy, screening, model organisms); a user of curated content to achieve research/business outcomes.
- Experience with a data platform such as lamin.ai.
- Experience with vector databases and search (e.g., Weaviate, FAISS, pgvector) and AI/LLM frameworks (e.g., LiteLLM, LangChain, LlamaIndex) for retrieval-augmented generation and agent workflows.
- Experience with OBO Foundry ontologies and modern frameworks such as LinkML, BioLink, and BioCypher, familiarity with graph database technologies (e.g., Neo4j, AWS Neptune) and semantic standards (OWL, RDF, SPARQL).
- Experience creating lightweight semantic layers and AI/LLM‑assisted curation workflows (LiteLLM, FastMCP).
The salary range for Cambridge, UK:
Exact compensation may vary based on skills, experience, and location.
Equality and equal opportunity statements apply to Altos Labs employees and applicants without regard to protected characteristics. Altos Labs provides equal employment opportunities to all employees and applicants for employment, without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Altos prohibits unlawful discrimination and harassment. This policy applies to all terms and conditions of employment.
Thank you for your interest in Altos Labs where we strive for a culture of scientific excellence, learning, and belonging.
Equal Opportunity Employment
Altos Labs promotes collaboration and scientific excellence and is committed to building a diverse and inclusive workplace. We cannot include site-only notices or excessive boilerplate here; please review the official Equal Opportunity statements in the posted job description for full details.
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Staff Software Engineer, Data Curation Institute of Computation / 24 September 2025 employer: Altos
Contact Detail:
Altos Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Software Engineer, Data Curation Institute of Computation / 24 September 2025
✨Tip Number 1
Network like a pro! Reach out to people in your field on LinkedIn or at industry events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Prepare for interviews by researching the company and its mission. Understand how your skills can contribute to their goals, especially in data curation and AI integration.
✨Tip Number 3
Showcase your projects! Whether it’s through a portfolio or GitHub, let your work speak for itself. Highlight any experience with data engineering or AI tools relevant to the role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Staff Software Engineer, Data Curation Institute of Computation / 24 September 2025
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the job description. Highlight your expertise in data curation, knowledge engineering, and any relevant projects you've worked on. We want to see how you can contribute to our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data curation and how your background makes you a great fit for our team. Be sure to mention specific experiences that relate to the responsibilities outlined in the job description.
Showcase Your Technical Skills: Since this role requires strong Python expertise and familiarity with data platforms, make sure to include any relevant technical skills in your application. If you've worked with ETL workflows or AI coding editors, let us know how you've used these tools to achieve results.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people. Plus, we love seeing candidates who take the initiative!
How to prepare for a job interview at Altos
✨Know Your Data Inside Out
Make sure you’re well-versed in the types of datasets you'll be working with, like genomics or proteomics. Familiarise yourself with the FAIR principles and how they apply to data curation. This will show your potential employer that you understand the core responsibilities of the role.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, and cloud platforms like AWS. Bring examples of ETL workflows you've built or data models you've designed. This practical demonstration of your skills can set you apart from other candidates.
✨Emphasise Collaboration
Since the role involves liaising between scientific and engineering teams, highlight any past experiences where you’ve successfully collaborated across disciplines. Share specific examples of how you translated complex research needs into actionable data solutions.
✨Demonstrate a Growth Mindset
Talk about your interest in AI and automation, especially regarding how you’ve used tools like Cursor or worked on agentic workflows. Showing that you’re eager to learn and adapt to new technologies will resonate well with the company’s innovative culture.