Description
drug discovery,ADMET,ML
At Apheris, we power federated data network in life sciences to address the data bottleneck in training highly performant ML models. Publicly available, molecular datasets are insufficient to train high-quality ML models that meet industry requirements. Our product addresses this by hosting networks where biopharma organizations collaboratively train higher quality models on their combined data. The Apheris product is a set of drug discovery applications - enriched with the proprietary data of network participants. Our federated computing infrastructure with built-in governance and privacy controls ensure that the data IP and ownership always stays with the data custodians.
As we are doubling down on ADMET (absorption, distribution, metabolism, excretion, and toxicity) use cases as a focus area within our drug discovery work, we are looking for a Principal ML Engineer to lead the technical direction for our ADMET models. This is a hands-on, high-impact role focused on advancing the state of the art in applying foundational models to drug discovery problems. You’ll work closely with our leadership team and will serve as the technical authority on ML modeling, architecture, and experimentation in this domain. While this is not a people management role, you will guide and mentor other engineers and researchers on a content level.
You should bring deep expertise in training and deploying different neural network architectures (graph neural networks, transformers, …) and data preparation for ADMET modelling and related tasks. You must also understand the application of these models within industrial drug discovery workflows and have a track record of setting strategy, breaking down complex technical problems, and delivering impactful ML systems.
If you want to be part of a mission-driven team building cutting-edge AI systems for life sciences – and you know what it takes to move from foundational models to domain-specific impact – this role is for you.
As we are doubling down on ADMET (absorption, distribution, metabolism, excretion, and toxicity) use cases as a focus area within our drug discovery work, we are looking for a Principal ML Engineer to lead the technical direction for our ADMET models. This is a hands-on, high-impact role focused on advancing the state of the art in applying foundational models to drug discovery problems. You’ll work closely with our leadership team and will serve as the technical authority on ML modeling, architecture, and experimentation in this domain. While this is not a people management role, you will guide and mentor other engineers and researchers on a content level.
You should bring deep expertise in training and deploying different neural network architectures (graph neural networks, transformers, …) and data preparation for ADMET modelling and related tasks. You must also understand the application of these models within industrial drug discovery workflows and have a track record of setting strategy, breaking down complex technical problems, and delivering impactful ML systems.
If you want to be part of a mission-driven team building cutting-edge AI systems for life sciences – and you know what it takes to move from foundational models to domain-specific impact – this role is for you.
- Drive the technical approach for ML applications in ADMET leveraging state of the art ML approaches like graph neural networks and transformers.
- Design and implement model extensions for specific tasks, including data distillation, benchmarking, and evaluation pipelines.
- Work with our customers and potentially academic partners to define data preprocessing, selection, and benchmarking strategies for novel training tasks involving ADMET data, including leveraging and harmonizing assay data from different sources.
- Build and maintain scalable, production-ready ML systems including training, inference, and deployment pipelines.
- Collaborate cross-functionally to ensure models address real-world drug discovery needs.
- Mentor and guide team members on a content level, supporting the planning and breakdown of complex ADMET modeling projects.
- Influence strategic decisions on model architecture, data infrastructure, and model deployment.
- Contribute to publications or open-source contributions where relevant.
What we expect from you
- By month 3: Develop a deep technical understanding of the Apheris product and how it maps to the current ADMET use-cases we are working on. Take ownership of an ADMET modeling stream. Build relationships with product and engineering leadership. Develop a roadmap and experiment plan for preparing data and adapting models to one high-value use case.
- By month 12: Lead multiple ML efforts in ADMET and demonstrate measurable progress in model performance and real-world impact. Mentor colleagues and set strategic direction for the domain.
- You have a PhD (or equivalent experience) in ML, computational biology, computational chemistry, or cheminformatics, and a track record of applying ML to real-world drug discovery problems.
- You have deep experience building and training ADMET machine learning models based on graph neural networks (e.g., ChemProp) and transformer approaches using PyTorch, PyTorch Lightning, or similar frameworks.
- You have deep experience in ADMET data, including an understanding of assay protocols and how to map protocols to each other, and can design scalable preprocessing, training, and evaluation workflows.
- You’ve delivered ML systems at scale, including CI/CD, model versioning, and GPU-based (distributed) training.
- You are comfortable working with modern MLOps tools and infrastructure, including Docker, Kubernetes, cloud platforms, and orchestration tools.
- You’re comfortable navigating complex technical landscapes and can break down and drive execution on ambitious modeling plans.
- You understand how ADMET models are used in the drug discovery lifecycle and can align your work to practical use cases.
- You have experience in federated learning, privacy-preserving ML, or secure model training.
- You’ve published in top-tier ML or biology journals/conferences (e.g., NeurIPS, ICML, Nature Methods, Bioinformatics)
- You’ve contributed to open-source ML or cheminformatics tooling.
- You have hands-on experience working with ADMET assays and DMPK stakeholders
- You have experience guiding technical direction in a fast-paced, research-oriented environment.
- Industry-competitive compensation, incl. early-stage virtual share options
- Remote-first working – work where you work best, whether from home or a co-working space near you
- Great suite of benefits, including a wellbeing budget, mental health benefits, a work-from-home budget, a co-working stipend and a learning and development budget
- Regular team lunches and social events
- Generous holiday allowance
- Quarterly All Hands meet-up at our Berlin HQ or a different European location
- A fun, diverse team of mission-driven individuals with a drive to see AI and ML used for good
- Plenty of room to grow personally and professionally and shape your own role
Apheris powers federated life sciences data networks, addressing the critical challenge of accessing proprietary data locked in silos due to IP and privacy concerns. Publicly available datasets are insufficient to train high-quality ML models that meet industry requirements. Our product addresses this by enabling life sciences organizations to collaboratively train higher quality models on complementary data from multiple parties. We are now doubling down on two key areas of interest: structural biology and ADMET.
Our interview process is split into three phases:- Initial Screening: If your application matches our requirements, we invite you to an initial video call to explore the fit. In this 30-45 minutes interview, you will get to know us and the role. The interviewer will be interested in your relevant experiences and skills, as well as answer any question on the company and the role itself that you may have.
- Deep Dive: In this phase, a domain expert from our team will assess your skills and knowledge required for the role by asking you about meaningful experiences or your solutions for specific scenarios in line with the role we are staffing.
- Final Interview: Finally, we invite you for up to three hours of targeted sessions with our founders, talking about our culture and meeting future co-workers on the ground.
Other Jobs from Apheris
Similar Jobs
AI Engineer/Lead AI Engineer
Remote
Hyderabad, India
Machine Learning Research Scientist/Engineer, AI/ML for Drug Discovery
Remote
San Diego, CA
Senior Full Stack Data Scientist
Remote
US
Senior Machine Learning Engineer (LLMs)
Remote
Poland
Software Engineer- AI/ML, AWS Neuron Distributed Training
Cupertino, CA
Santa Clara, CA
There are more than 50,000 engineering jobs:
Subscribe to membership and unlock all jobs
Engineering Jobs
60,000+ jobs from 4,500+ well-funded companies
Updated Daily
New jobs are added every day as companies post them
Refined Search
Use filters like skill, location, etc to narrow results
Become a member
🥳🥳🥳 452 happy customers and counting...
Overall, over 80% of customers chose to renew their subscriptions after the initial sign-up.
To try it out
For active job seekers
For those who are passive looking
Cancel anytime
Frequently Asked Questions
- We prioritize job seekers as our customers, unlike bigger job sites, by charging a small fee to provide them with curated access to the best companies and up-to-date jobs. This focus allows us to deliver a more personalized and effective job search experience.
- We've got about 70,000 jobs from 5,000 vetted companies. No fake or sleazy jobs here!
- We aggregate jobs from 5,000+ companies' career pages, so you can be sure that you're getting the most up-to-date and relevant jobs.
- We're the only job board *for* software engineers, *by* software engineers… in case you needed a reminder! We add thousands of new jobs daily and offer powerful search filters just for you. 🛠️
- Every single hour! We add 2,000-3,000 new jobs daily, so you'll always have fresh opportunities. 🚀
- Typically, job searches take 3-6 months. EchoJobs helps you spend more time applying and less time hunting. 🎯
- Check daily! We're always updating with new jobs. Set up job alerts for even quicker access. 📅
What Fellow Engineers Say
