Apheris on cord

Apheris

Senior ML Engineer

External position
Remote in Europe
Hiring internally for Apheris?
Computer and Network Security
Solve humanity's greatest challenges through collaborative data ecosystems.
Posted
a week ago
Checked
cord regularly checks that external positions are still open
2 days ago

Skills & Experience

Job roles: Machine Learning Engineer
Experience level: Senior
Core skills considered: Python, Machine Learning, PyTorch
Other skills considered: Data Pipelines, Kubernetes

Logistics

Base salary: Undisclosed
Some companies on cord are unable to disclose salaries publicly due to internal company policies. Message the company for salary information.
Employment type: Permanent
Remote working: Remote
Work from: Within Europe
Visa sponsorship: Not available

Job Description

We're looking for a senior ML engineer to own the training and evaluation pipelines behind our ADMET and toxicity networks - the machinery that turns partner data into trained, benchmarked, released models, run after run.

This is a hands-on engineering role at the point where molecular ML meets federation. Your code runs inside partner environments, on data you cannot see, alongside scientists at some of the largest pharma companies in the world.

You'll work closely with the scientific lead for toxicity: they own what we model and why, you own how it gets built, validated, evaluated and shipped - reliably enough that a partner will stake a drug program on the result.

The ADMET network is live and expanding into toxicity. You'll be building the pipelines that expansion runs on.


What you will do

  • Own the model pipelines end to end. Take partner data from landing to released, benchmarked model weights - data preparation, training, evaluation, release - for ADMET and toxicity endpoints.
  • Build the validation that partners run alongside us. Schema and data contracts, validators that return actionable errors, and QC/profiling reports that a partner can act on without us seeing their raw data.
  • Make federated runs reproducible and auditable. Versioned configs, pinned data snapshots, provenance for every released model - so we can say exactly what produced a given set of weights.
  • Build evaluation that survives scrutiny. Leakage-safe splitting, held-out benchmarks and honest performance reporting, so the numbers we put in front of partners hold up.
  • Harden research into product. Turn prototypes and research code into tested, modular systems, and hand them cleanly to engineering for scaling into Foundry.
  • Work across the boundary. Translate scientific requirements into pipeline behavior with the science team, and surface data or modeling risks early to partners and internally.

What we expect from you

  • 5+ years building ML systems in Python, with genuine software engineering discipline: version control, tested modular code, code review, and interfaces other people can use.
  • Hands-on molecular ML or cheminformatics - RDKit, fingerprints and descriptors, or graph/transformer models - applied to property, activity or toxicity prediction.
  • You have built training and evaluation pipelines that other people run, not one-off notebooks.
  • You understand how molecular ML goes wrong: data leakage, split design, applicability domain, dataset shift, and over-optimistic benchmarks - and you design against them by default.
  • You can write validators and data contracts that hold up under partial visibility, where you cannot inspect the data yourself.
  • Comfortable with PyTorch or an equivalent modern ML stack.
  • You work well with scientists: you can take an ambiguous scientific requirement and turn it into defined, testable pipeline behavior.

Nice to have

  • Federated learning, privacy-preserving ML, or other multi-party training environments.
  • ML Ops or ML infrastructure experience, particularly Kubernetes-based training, evaluation or deployment workflows.
  • Production-grade model delivery in regulated, enterprise, pharmaceutical or biotech settings.
  • Familiarity with public ADMET, toxicity and bioactivity data resources (ChEMBL, Tox21, ToxCast) and the gotchas in each.
  • Open-source contributions or a publication record in cheminformatics, molecular ML, or applied machine learning.

Company Benefits

  • High degree of empowerment and autonomy;
  • Impact- you will contribute to developing an entirely new discipline that will change how value is unlocked from data;
  • A fun and diverse team of smart and very driven people;
  • Industry-competitive compensation;
  • Employee share option scheme;
  • Generous holiday allowance
  • Inspiring office space in the heart of Berlin;
  • Remote-first plus a quarterly all-hands
Senior ML Engineer at Apheris
Position posted a week ago

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Starling Bank on cord

Starling Bank

Full Stack Engineer (ML Ops)

London, UK
FinTech · Banking · Finance
A better bank for everyone
Active
over 6 months ago
Responds to
0% of requests
Responds in
1h 55m
Requests
7 pending

Skills & Experience

Job roles: Full Stack
Experience level: Mid, Senior
Core skills considered: Java, React, Redux, AWS, JavaScript

Logistics

Base salary: £70K - £110K
Employment type: Permanent
Remote working: Hybrid (up to 2 remote days p/w)
Visa sponsorship: Not available

Job Description

Starling is the UK’s first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.

Starling is the UK’s first and leading digital bank on a mission to fix banking! We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way.

We’re a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We’re a bank, but better: fairer, easier to use and designed to demystify money for everyone. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices.

Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together!

The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.

Hybrid Working

We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person. We don't like to mandate how much you visit the office and work from home, that's to be agreed upon between you and your manager.

Our Data Environment

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech.

We are looking for talented data professionals at all levels to join the team. We value people being engaged and caring about customers, caring about the code they write and the contribution they make to Starling. People with a broad ability to apply themselves to a multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good.

Requirements

We have built our entire banking platform in house and mostly in Java. We are looking for people who want to work on building the tooling that is used by our engineers on a daily basis.

We are looking for people who are truly full stack, and are as comfortable polishing their javascript front end as they are debugging the innards of their java applications database interactions, or standing up infrastructure with terraform. We are looking for people who can:

  • Design REST apis.
  • Code backend services, ideally using Java, or another other server side compiled language.
  • Develop modern front ends, ideally using React and Redux.
  • Get their code into the cloud and support it there, ideally on AWS.
  • Believe in clean coding, simple solutions, automated testing and continuous deployment.
  • Like to take ownership of a feature from the original idea through to live.
  • Think (like us) that a small number of empowered developers is the right way to deliver software.

Company Benefits

  • 33 days holiday (including flexible bank holidays)
  • An extra day’s holiday for your birthday
  • 16 hours paid volunteering time a year
  • Part-time and/or flexible hours available for most roles
  • Salary sacrifice, company enhanced pension scheme
  • Life insurance at 4x your salary
  • Hybrid/remote working
  • Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr&Mrs Smith and Peloton
  • Generous family-friendly policies
  • Varied social groups set up and run by our employees
  • Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks
  • Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing

Full details are available on our careers site

Interview Process

Interviewing is a two way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general you can expect the below, following a chat with one of our Talent Team:

  • Stage 1 - 30 mins with one of the team
  • Stage 2 - Take home challenge
  • Stage 3 - 90 mins technical interview with two team members
  • Stage 3 - 45 min final with an executive and a member of the people team
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