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- 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 in biotechnology while working with cutting-edge technology.
- Qualifications: PhD or equivalent experience in relevant fields; strong Python and data engineering skills.
- Other info: Be part of a diverse team focused on collaboration and belonging.
The predicted salary is between 43200 - 72000 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.
Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice).
This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.
Equal Opportunity Employment
We value collaboration and scientific excellence. We believe that diverse perspectives and a culture of belonging are foundational to scientific innovation and inquiry. At Altos Labs, 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 an inclusive environment.
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, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
Thank you for your interest in Altos Labs where we strive for a culture of scientific excellence, learning, and belonging.
Note: Altos Labs will not ask you to download a messaging app for an interview or outlay your own money to get started as an employee. If this sounds like your interaction with people claiming to be with Altos, it is not legitimate and has nothing to do with Altos. Learn more about a common job scam at https://www.linkedin.com/pulse/how-spot-avoid-online-job-scams-biron-clark/
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Staff Software Engineer, Data Curation employer: Altos Labs
Contact Detail:
Altos Labs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Software Engineer, Data Curation
✨Tip Number 1
Network like a pro! Reach out to current employees at Altos Labs on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing the Staff Software Engineer role. Personal connections can make a huge difference!
✨Tip Number 2
Prepare for the interview by brushing up on your Python skills and data curation knowledge. Be ready to discuss how you’ve tackled complex datasets in the past. Show us that you can not only handle data but also make it FAIR!
✨Tip Number 3
Don’t just talk about your technical skills; highlight your collaborative spirit! Altos values diverse perspectives, so share examples of how you’ve worked with cross-functional teams to achieve common goals.
✨Tip Number 4
Finally, apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the Altos mission. Let’s get you on board!
We think you need these skills to ace Staff Software Engineer, Data Curation
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Staff Software Engineer role. Highlight your expertise in data curation, Python, and any relevant projects that showcase your ability to work with complex datasets.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about our mission at Altos. Share specific examples of how your background in biological sciences or software engineering can contribute to our goals in cell rejuvenation and data curation.
Showcase Your Technical Skills: Don’t shy away from detailing your technical prowess! Mention your experience with ETL workflows, cloud platforms like AWS, and any AI tools you've used. This is your chance to impress us with your hands-on knowledge.
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!
How to prepare for a job interview at Altos Labs
✨Know Your Data Inside Out
Make sure you’re well-versed in the types of datasets mentioned in the job description, like genomics and proteomics. Familiarise yourself with how to clean, normalise, and annotate these datasets, as well as the tools and vocabularies used in data curation.
✨Showcase Your Python Skills
Since strong Python expertise is a must, prepare to discuss your experience with data modelling and processing. Bring examples of past projects where you’ve built ETL/ELT workflows or used Python for data curation, and be ready to demonstrate your problem-solving approach.
✨Understand the Importance of FAIR Data
Brush up on the principles of making data Findable, Accessible, Interoperable, and Reusable (FAIR). Be prepared to discuss how you would apply these principles in your role and share any relevant experiences where you’ve improved data governance or quality.
✨Emphasise Collaboration and Communication
As a key technical liaison, your ability to communicate complex research needs is crucial. Prepare examples of how you’ve successfully collaborated with cross-functional teams in the past, and think about how you can contribute to fostering an inclusive environment at Altos.