Home › Companies › Apheris › Technical Lead – Large Molecule AI Systems
Technical Lead – Large Molecule AI Systems
Apheris · Remote (UTC +/- 2 hrs) · Remote · Active · Personio
Job facts
| Field | Value |
|---|---|
| Company | Apheris |
| Title | Technical Lead – Large Molecule AI Systems |
| Normalized title | - |
| Department / team | Engineering & Product / Research and Science |
| Location | Remote (UTC +/- 2 hrs) |
| Work model | Remote / Remote |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Personio |
| Posted / first seen | 2026-05-27 / 2026-05-30 |
| Changed / last seen | 2026-05-30 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Apheris. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Personio. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| Department jobs | Active postings in Engineering & Product. | Open |
| Work model jobs | Active Remote postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Apheris |
| Source | 946c6a21-be70-4465-a5f8-0b3372e31053 |
| ATS provider | Personio |
Description
About Apheris
At Apheris , we are building the future of how AI is applied in pharmaceutical R&D.
We enable leading pharmaceutical teams to discover and develop drugs faster. We host the industry’s largest federated data networks for drug discovery AI, spanning co-folding, ADMET, and antibody developability.
Across these networks, models are trained on proprietary industry datasets to achieve higher performance and broader applicability while keeping data control and IP protected. We deliver these superior models through drug discovery applications that enable teams to run them at scale, further customize them, and integrate them into existing R&D workflows.
AI Structural Biology (AISB) Network : Pharmaceutical companies collaborate in the field of co-folding, structure-based binding affinity predictions and antibody design. ADMET Network: Pharmaceutical and biotech companies collaborate to improve small-molecule property prediction and expand to further drug modalities. Antibody Developability Network: Pharma partners collaborate to federate historical and purpose-built antibody developability datasets for secure ML training, without data leaving each partner’s environment.
About the role
We are looking for a technical lead to own delivery of our large molecule AI model programs. This is a hands-on leadership role at the intersection of foundation models, structural biology, protein engineering, and federated learning. You will lead teams building and operationalizing large-scale ML systems for antibody modeling , co-folding, developability prediction, and biologics discovery.
You will turn ambitious scientific goals into reliable model systems that can be evaluated, released, and used in real drug discovery workflows. You will set technical direction, drive execution, challenge modeling decisions, and turn ambiguity into executable plans, while managing risks and dependencies, mentoring senior engineers and ML scientists, and getting into technical depth when needed. We are looking for someone who has led demanding ML delivery before and knows how to move from research -led or open-source prototypes to robust model systems.
What you will do
Lead teams building and delivering federated large molecule AI systems , staying hands-on across antibody modeling , co-folding, binder prediction, and developability. Build and implement ML applications large biomolecular foundation models such as OpenFold , Boltz-2 and ESM. Own delivery of these against committed milestones and ensure high-quality model releases ship on time. Translate ambiguous scientific and technical goals into clear plans, priorities, workstreams, and decisions. Guide evaluation decisions and build on them to deliver results packages to external stakeholders. Surface risks, blockers, bugs, timeline changes, and technical trade-offs early, with clear recommendations. Align consortium members on objectives , evaluation criteria, data requirements, timelines, and delivery expectations. Work with product, engineering, research, and leadership to ensure application requirements shape the model roadmap.
What we expect from you
You have a PhD, MSc, or equivalent experience in a relevant field, plus 5+ years applying ML to complex scientific or biological problems, ideally in structural biology, antibody engineering, biologics discovery, developability prediction, binder prediction or protein design . You have hands-on experience with modern ML systems in Python and PyTorch , and have worked with or extended large-scale models such as OpenFold , AlphaFold, Boltz, ESM, or similar. You have MLOps or ML infrastructure experience, particularly with Kubernetes-based training, evaluation, or deployment workflows. You can define success criteria, validate model quality, and ensure ML releases are robust enough for real-world use. You have led delivery of complex ML projects, including setting technical direction, managing risks and dependencies, and driving teams toward high-quality releases. You are comfortable operating as a player-coach: mentoring engineers and ML scientists while contributing directly to modeling , experimentation, or architecture when needed. You can work effectively with product, research, leadership, customers, and scientific stakeholders to turn ambiguous requirements into clear technical plans.
Nice to have
You have experience with federated learning, privacy-preserving ML, distributed training, or other multi-party training environments. You have worked on production-grade model delivery in regulated, enterprise, pharmaceutical, biotech, or other high-trust environments. You have a publication record in top-tier ML, computational biology, or structural biology venues such as NeurIPS , ICML, ICLR, ISMB, RECOMB, or similar.
What we offer you
Industry-competitive compensation, including early-stage virtual share options Remote-first working – work where you work best Wellbeing budget, mental health support, work-from-home budget, co-working stipend, and learning budget Generous holiday allowance Office Days at our Berlin HQ or a different European location (3x per year) A high- calibre , execution-focused team with experience from leading organizations
Full job record
| Job ID | 12c759d83ad5886ee76f217b50ea4ce64d14d8ab |
| Org ID | 26b9bc0d-53ed-4379-bdf9-25ba8ee4678a |
| Source ID | 946c6a21-be70-4465-a5f8-0b3372e31053 |
| Board ID | 946c6a21-be70-4465-a5f8-0b3372e31053 |
| Provider | personio |
| Provider Job Key | 2648931 |
| Title | Technical Lead – Large Molecule AI Systems |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | Remote (UTC +/- 2 hrs) |
| Department | Engineering & Product |
| Team | Research and Science |
| Employment Type | full_time |
| Workplace Type | remote |
| Remote Policy | remote |
| Country | Remote (UTC +/- 2 hrs) |
| Region | — |
| City | — |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://apheris.jobs.personio.com/job/2648931?language=en |
| Apply URL | https://apheris.jobs.personio.com/job/2648931?language=en |
| First Seen At | 2026-05-30 05:58:28Z |
| Last Seen At | 2026-06-06 07:46:05Z |
| Last Checked At | 2026-06-06 07:46:05Z |
| Last Changed At | 2026-05-30 05:58:28Z |
| Inactive At | — |
| Source Posted At | 2026-05-27 11:32:33Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=personio/board=apheris.com/date=2026-06-06/2026-06-06T07-46-04-323Z-d2d48bf5a99c9dacd3d9fa9531387d23820871ea0bc9885bad3dd44f97e110fa.json |
Event Fields
{
"content_hash": "44b41cdae940ff026cf6a0d871646d66c0ec4e4a371da8d041174b996810b69d",
"source_hash": "d643cc32d2d03244d3221a21673e81a2c40f7361e2bbaf7dc582300513722821",
"last_changed_at": "2026-05-30T05:58:28.849Z",
"active_status": "active"
}Parsed Structured
{
"language": "en",
"location": {
"raw": "Remote (UTC +/- 2 hrs)",
"city": null,
"region": null,
"country": "Remote (UTC +/- 2 hrs)",
"is_remote": true,
"confidence": 0.8
},
"salary_max": null,
"salary_min": null,
"inferred_at": "2026-06-06T07:46:05.048Z",
"launch_scope": {
"reason": "personio_production_catalog",
"included": true,
"location": {
"raw": "Remote (UTC +/- 2 hrs)",
"city": null,
"region": null,
"country": "Remote (UTC +/- 2 hrs)",
"is_remote": true,
"confidence": 0.8
},
"countries": [
"Remote (UTC +/- 2 hrs)"
]
},
"remote_policy": "remote",
"salary_period": null,
"workplace_type": "remote",
"salary_currency": null
}Extensions
{}Native Structured
{
"id": "2648931",
"name": "Technical Lead – Large Molecule AI Systems",
"office": "Remote (UTC +/- 2 hrs)",
"keywords": [],
"schedule": "full-time",
"createdAt": "2026-05-27T11:32:33+00:00",
"seniority": "experienced",
"department": "Engineering & Product",
"occupation": "biological_and_chemical_research",
"subcompany": null,
"employmentType": "permanent",
"jobDescriptions": [
{
"name": "About Apheris",
"value": "<p style=\"margin:0px 0px 13.3333px;padding:0px;font-weight:normal;font-style:normal;background-color:transparent;color:rgb(75,84,86);text-align:left;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">At </span><span style=\"margin:0px;padding:0px;\">Apheris</span><span style=\"margin:0px;padding:0px;\">, we are building the future of how AI is applied in pharmaceutical R&D.</span></span><span style=\"margin:0px;padding:0px;background-color:rgb(198,198,198);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;color:rgb(75,84,86);\"> </span></p><p style=\"margin:0px 0px 13.3333px;padding:0px;font-weight:normal;font-style:normal;background-color:transparent;color:rgb(75,84,86);text-align:left;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">We enable leading pharmaceutical teams to discover and develop drugs faster. We host the industry’s largest federated data networks for drug discovery AI, spanning co-folding, ADMET, and antibody developability.</span></span><span style=\"margin:0px;padding:0px;background-color:rgb(198,198,198);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;color:rgb(75,84,86);\"> </span></p><p style=\"margin:0px 0px 13.3333px;padding:0px;font-weight:normal;font-style:normal;background-color:transparent;color:rgb(75,84,86);text-align:left;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">Across these networks, models are trained on proprietary industry datasets to achieve higher performance and broader applicability while keeping data control and IP protected. We deliver these superior models through drug discovery applications that enable teams to run them at scale, further customize them, and integrate them into existing R&D workflows. </span></span><span style=\"margin:0px;padding:0px;background-color:rgb(198,198,198);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;color:rgb(75,84,86);\"> </span></p><ul style=\"list-style-type:disc;margin-left:0px;\"><li style=\"margin-left:24px;\"><a style=\"margin:0px;padding:0px;text-decoration:none;color:inherit;\" target=\"_blank\" href=\"https://eur05.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.apheris.com%2Fjoin-a-network%2Faisb&data=05%7C02%7Cm.roehm%40apheris.com%7C520931505f4d482bd73908de55d7608e%7Cb6d171875373488081f05b051498b5ba%7C0%7C0%7C639042581002262641%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=IxRzlz7SNqBLsu67gZ3e3cbcO2SkZeL83TzFqzrXKfQ%3D&reserved=0\" rel=\"noreferrer noopener\"><span style=\"margin:0px;padding:0px;color:rgb(150,96,125);font-size:13px;text-decoration:underline;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">AI Structural Biology (AISB) Network</span></span></a><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">:</span><span style=\"margin:0px;padding:0px;\">Pharmaceutical</span><span style=\"margin:0px;padding:0px;\">companies collaborate in the field of co-folding, structure-based binding affinity</span><span style=\"margin:0px;padding:0px;\">predictions</span><span style=\"margin:0px;padding:0px;\">and antibody design.</span></span></li><li style=\"margin-left:24px;\"><a style=\"margin:0px;padding:0px;text-decoration:none;color:inherit;\" target=\"_blank\" href=\"https://www.apheris.com/join-a-network/admet\" rel=\"noreferrer noopener\"><span style=\"margin:0px;padding:0px;color:rgb(150,96,125);font-size:13px;text-decoration:underline;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">ADMET Network:</span></span></a><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">Pharmaceutical and biotech companies</span><span style=\"margin:0px;padding:0px;\">collaborate to improve small-molecule property prediction and expand to further drug modalities.</span></span></li><li style=\"margin-left:24px;\"><a style=\"margin:0px;padding:0px;text-decoration:none;color:inherit;\" target=\"_blank\" href=\"https://eur05.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.apheris.com%2Fjoin-a-network%2Fantibody-developability-consortium&data=05%7C02%7Cm.roehm%40apheris.com%7C520931505f4d482bd73908de55d7608e%7Cb6d171875373488081f05b051498b5ba%7C0%7C0%7C639042581002275354%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=aWyaHuX319ZMV%2F7L%2FA8avybqdcyVV%2B1KQ0oPUHlRFqI%3D&reserved=0\" rel=\"noreferrer noopener\"><span style=\"margin:0px;padding:0px;color:rgb(66,144,154);font-size:13px;text-decoration:underline;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">Antibody Developability Network:</span></span></a><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">Pharma partners collaborate to federate historical and purpose-built antibody developability datasets for secure ML training, without data leaving each partner’s environment.</span></span></li></ul>"
},
{
"name": "About the role",
"value": "<p style=\"margin:0px 0px 13.3333px;padding:0px;font-weight:normal;font-style:normal;background-color:transparent;color:rgb(75,84,86);text-align:left;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">We are looking for a technical lead to own delivery of our </span><span style=\"margin:0px;padding:0px;\">large molecule </span><span style=\"margin:0px;padding:0px;\">AI model programs.</span></span><span style=\"margin:0px;padding:0px;font-size:13px;line-height:17.25px;font-family:'WordVisiCarriageReturn_MSFontService', 'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;color:rgb(75,84,86);\"><span style=\"margin:0px;padding:0px;\"> </span><br style=\"margin:0px;padding:0px;\"></span><span style=\"margin:0px;padding:0px;font-size:13px;line-height:17.25px;font-family:'WordVisiCarriageReturn_MSFontService', 'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;color:rgb(75,84,86);\"><span style=\"margin:0px;padding:0px;\"> </span><br style=\"margin:0px;padding:0px;\"></span><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">This is a hands-on leadership role at the intersection of foundation models, structural biology, protein engineering, and federated learning. You will lead teams building and operationalizing large-scale ML systems for antibody </span><span style=\"margin:0px;padding:0px;\">modeling</span><span style=\"margin:0px;padding:0px;\">, co-folding, developability prediction, and biologics discovery.</span></span><span style=\"margin:0px;padding:0px;background-color:rgb(198,198,198);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;color:rgb(75,84,86);\"> </span></p><p style=\"margin:0px 0px 13.3333px;padding:0px;font-weight:normal;font-style:normal;background-color:transparent;color:rgb(75,84,86);text-align:left;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">You will turn ambitious scientific goals into reliable model systems that can be evaluated, released, and used in real drug discovery workflows.</span></span><span style=\"margin:0px;padding:0px;font-size:13px;line-height:17.25px;font-family:'WordVisiCarriageReturn_MSFontService', 'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;color:rgb(75,84,86);\"><span style=\"margin:0px;padding:0px;\"> </span><br style=\"margin:0px;padding:0px;\"></span><span style=\"margin:0px;padding:0px;font-size:13px;line-height:17.25px;font-family:'WordVisiCarriageReturn_MSFontService', 'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;color:rgb(75,84,86);\"><span style=\"margin:0px;padding:0px;\"> </span><br style=\"margin:0px;padding:0px;\"></span><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">You will set technical direction, drive execution, challenge </span><span style=\"margin:0px;padding:0px;\">modeling</span><span style=\"margin:0px;padding:0px;\"> decisions, and turn ambiguity into executable plans, while managing risks and dependencies, mentoring senior engineers and ML scientists, and getting into technical depth when needed.</span></span><span style=\"margin:0px;padding:0px;font-size:13px;line-height:17.25px;font-family:'WordVisiCarriageReturn_MSFontService', 'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;color:rgb(75,84,86);\"><span style=\"margin:0px;padding:0px;\"> </span><br style=\"margin:0px;padding:0px;\"></span><span style=\"margin:0px;padding:0px;font-size:13px;line-height:17.25px;font-family:'WordVisiCarriageReturn_MSFontService', 'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;color:rgb(75,84,86);\"><span style=\"margin:0px;padding:0px;\"> </span><br style=\"margin:0px;padding:0px;\"></span><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">We are looking for someone who has led demanding ML delivery before and knows how to move from research</span><span style=\"margin:0px;padding:0px;\">-led or open-source</span><span style=\"margin:0px;padding:0px;\"> prototypes to robust model systems.</span></span><span style=\"margin:0px;padding:0px;background-color:rgb(198,198,198);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;color:rgb(75,84,86);\"> </span></p>"
},
{
"name": "What you will do",
"value": "<ul style=\"list-style-type:disc;margin-left:0px;\"><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">Lead teams building and delivering federated large molecule AI systems</span><span style=\"margin:0px;padding:0px;\">, staying hands-on</span><span style=\"margin:0px;padding:0px;\">across antibody</span><span style=\"margin:0px;padding:0px;\">modeling</span><span style=\"margin:0px;padding:0px;\">, co-folding, binder prediction, and developability.</span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">Build and implement</span><span style=\"margin:0px;padding:0px;\"> ML applications</span><span style=\"margin:0px;padding:0px;\">large biomolecular foundation models</span><span style=\"margin:0px;padding:0px;\">such as</span><span style=\"margin:0px;padding:0px;\">OpenFold</span><span style=\"margin:0px;padding:0px;\">, Boltz-2</span><span style=\"margin:0px;padding:0px;\"> and ESM.</span><span style=\"margin:0px;padding:0px;\">Own delivery of these against committed milestones and ensure high-quality model releases ship on time.</span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">Translate ambiguous scientific and technical goals into clear plans, priorities, workstreams, and decisions.</span><span style=\"margin:0px;padding:0px;\">Guide evaluation decisions</span><span style=\"margin:0px;padding:0px;\">and build on them to deliver</span><span style=\"margin:0px;padding:0px;\">results</span><span style=\"margin:0px;padding:0px;\">packages to external stakeholders.</span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">Surface risks, blockers, bugs, timeline changes, and technical trade-offs early, with clear recommendations.</span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">Align consortium members on</span><span style=\"margin:0px;padding:0px;\">objectives</span><span style=\"margin:0px;padding:0px;\">, evaluation criteria, data requirements, timelines, and delivery expectations.</span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">Work with product, engineering, research, and leadership to ensure application requirements shape the model roadmap.</span></span></li></ul>"
},
{
"name": "What we expect from you",
"value": "<div style=\"margin:0px;padding:0px;color:rgb(0,0,0);font-family:'Segoe UI', 'Segoe UI Web', Arial, Verdana, sans-serif;font-size:12px;font-style:normal;font-weight:400;background-color:rgb(255,255,255);\"><ul style=\"list-style-type:disc;margin-left:0px;\"><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">You have a PhD, MSc, or equivalent experience in a relevant field, plus 5+ years applying ML to complex scientific or biological problems, ideally in</span><span style=\"margin:0px;padding:0px;\">structural biology, antibody engineering, biologics discovery, developability prediction, binder</span><span style=\"margin:0px;padding:0px;\">prediction</span><span style=\"margin:0px;padding:0px;\">or</span><span style=\"margin:0px;padding:0px;\">protein design</span><span style=\"margin:0px;padding:0px;\">.</span></span></li></ul></div><div style=\"margin:0px;padding:0px;color:rgb(0,0,0);font-family:'Segoe UI', 'Segoe UI Web', Arial, Verdana, sans-serif;font-size:12px;font-style:normal;font-weight:400;background-color:rgb(255,255,255);\"><ul style=\"list-style-type:disc;margin-left:0px;\"><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">You have hands-on experience with modern ML systems in Python and</span><span style=\"margin:0px;padding:0px;\">PyTorch</span><span style=\"margin:0px;padding:0px;\">, and have worked with or extended large-scale models such as</span><span style=\"margin:0px;padding:0px;\">OpenFold</span><span style=\"margin:0px;padding:0px;\">, AlphaFold, Boltz, ESM, or similar.</span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">You have</span><span style=\"margin:0px;padding:0px;\">MLOps</span><span style=\"margin:0px;padding:0px;\">or ML infrastructure experience, particularly with Kubernetes-based training, evaluation, or deployment workflows.</span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">You can define success criteria,</span><span style=\"margin:0px;padding:0px;\">validate</span><span style=\"margin:0px;padding:0px;\">model quality, and ensure ML releases are robust enough for real-world use.</span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">You have led delivery of complex ML projects, including setting technical direction, managing risks and dependencies, and driving teams toward high-quality releases.</span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">You are comfortable operating as a player-coach: mentoring engineers and ML scientists while contributing directly to</span><span style=\"margin:0px;padding:0px;\">modeling</span><span style=\"margin:0px;padding:0px;\">, experimentation, or architecture when needed.</span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">You can work effectively with product, research, leadership, customers, and scientific stakeholders to turn ambiguous requirements into clear technical plans.</span></span></li></ul></div>"
},
{
"name": "Nice to have",
"value": "<ul style=\"list-style-type:disc;margin-left:0px;\"><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">You have experience with federated learning, privacy-preserving ML, distributed training, or other multi-party training environments.</span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">You have worked on production-grade model delivery in regulated, enterprise, pharmaceutical, biotech, or other high-trust environments.</span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">You have a publication record in top-tier ML, computational biology, or structural biology venues such as</span><span style=\"margin:0px;padding:0px;\">NeurIPS</span><span style=\"margin:0px;padding:0px;\">, ICML, ICLR, ISMB, RECOMB, or similar.</span></span></li></ul>"
},
{
"name": "What we offer you",
"value": "<ul style=\"list-style-type:disc;margin-left:0px;\"><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">Industry-competitive compensation, including early-stage virtual share options </span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">Remote-first working – work where you work best </span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">Wellbeing budget, mental health support, work-from-home budget, co-working stipend, and learning budget </span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">Generous holiday allowance </span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">Office Days at our Berlin HQ or a different European location (3x per year) </span></span></li><li style=\"margin-left:24px;\"><span style=\"margin:0px;padding:0px;color:rgb(75,84,86);font-size:13px;line-height:17.25px;font-family:'Univers Light', 'Univers Light_EmbeddedFont', 'Univers Light_MSFontService', sans-serif;\"><span style=\"margin:0px;padding:0px;\">A high-</span><span style=\"margin:0px;padding:0px;\">calibre</span><span style=\"margin:0px;padding:0px;\">, execution-focused team with experience from leading organizations </span></span></li></ul>"
}
],
"occupationCategory": "r_and_d_and_science",
"recruitingCategory": "Research and Science"
}Get this page with API
Rendered from the bluedoor Job Postings API. Reproduce it:
GET https://api.bluedoor.sh/job-postings/v1/jobs/12c759d83ad5886ee76f217b50ea4ce64d14d8ab?include=descriptionJSONGET https://api.bluedoor.sh/job-postings/v1/orgs/26b9bc0d-53ed-4379-bdf9-25ba8ee4678aJSONGET https://api.bluedoor.sh/job-postings/v1/sources/946c6a21-be70-4465-a5f8-0b3372e31053JSONGET https://api.bluedoor.sh/job-postings/v1/jobs/12c759d83ad5886ee76f217b50ea4ce64d14d8ab/eventsJSON