Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowPosted 77 days ago

Senior ML Research Engineer

apheris7 open roles

Where
Remote (UTC +/- 2 hrs)
Work mode
Remote
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowSenior ML Research Engineerapheris · Remote (UTC +/- 2 hrs)

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on apheris's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

13.4% of postings close within 7 days. Measured by our own scanner across the market. apheris postings stay open a median of 14 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.6%3 days
  3. 13.4%7 days
  4. 21.6%14 days
  5. 36.2%30 days
  6. 59.0%60 days
This job: posted 77 days ago

apheris median: 14 days open

The posting

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 into further drug modalities.
  • Antibody Developability Network: Pharma partners collaborate to federate historical and purpose-built antibody developability data sets for secure ML training, without data leaving each partner’s environment.

About the role

We are looking for a Senior Machine Learning Research Engineer to help drive the research and development of machine learning models for molecular and structural biology.

This is a hands-on role at the intersection of foundation models, structural biology, and federated learning. You'll execute research projects, turning ambitious scientific goals into frontier ML models that can be evaluated, released, and used in real drug-discovery workflows.

What you will do

  • Develop and improve ML models in molecular and structural biology, such as co-folding and binding affinity models, for drug design applications and workflows, driving them from ideation through prototyping iterations to robust tooling.
  • Build effective benchmarking and evaluation strategies for model evaluation and iterate and refine existing modelling approaches based on data-driven insights.
  • Diagnose and resolve data quality and pipeline issues that affect model quality.
  • Stay up to date with a rapidly evolving research literature and identify best public approaches to aid in research and development.
  • Collaborate with customers, partner-facing engineers, and external collaborators to support real-world drug design use cases.

What we expect from you

  • You have a PhD or MSc in machine learning, computational biology, computational chemistry, bioinformatics, physics, or a related field, with at least 2 years of professional experience applying ML to scientific problems.
  • You have hands-on experience training, fine-tuning and extending deep learning models for molecular or protein structure modelling.
  • You are able to rigorously interrogate ML models, their training, and scientific benchmarks, and translate insights into impactful improvements.
  • You are an expert in Python and PyTorch, can produce reliable and clean code, and are comfortable with multi-GPU and distributed training.
  • You have deep familiarity with structural biology and protein–ligand data formats, quality metrics and tooling.
  • You proactively identify opportunities to contribute scientifically in order to impact the organizational goals.

Nice to have

  • You have experience in federated learning, privacy-preserving ML, or secure model training.
  • You have experience developing ML models for drug design in pharmaceutical or biotech environments.
  • You have published at top-tier ML or structural biology venues or have contributed to open-source projects in that space.

What we offer you

  • Industry-competitive compensation, including 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
  • Generous holiday allowance
  • Office Days at our Berlin HQ or a different European location (3x a year)
  • A fun, diverse team of mission-driven individuals with experience across leading organizations and a drive to see AI and ML used for good
From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against apheris's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on apheris's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    apheris's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.