Panakeia on cord

Panakeia

Machine Learning Engineer

External position
London, UK
Hiring internally for Panakeia?
Machine Learning and AI · HealthTech
Rapid, instrument-free precision cancer diagnostics
Posted
a month ago
Checked
cord regularly checks that external positions are still open
2 days ago

Skills & Experience

Job roles: Machine Learning Engineer
Experience level: Mid, Senior
Core skills considered: Python, Deep Learning, Machine Learning, Computer Vision
Other skills considered: Data Analysis, Data Pipelines, Cloud Computing, Docker

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: Hybrid
Visa sponsorship: Not available

Job Description

As an ML Engineer at Panakeia, you will sit at the critical junction of research, engineering and product delivery. You will be responsible for building, training, and validating the machine learning models that power our platform and clinical products at scale.

You will own a clinical product end-to-end, from the initial exploratory phase through to delivery, while contributing to the platform and the wider set of solutions built on it. The role blends hands-on model development, rigorous experimentation, and turning ideas from research into working code - with a focus on models that generalise well and are robust for clinical use.

You will work across our multi-disciplinary team of AI, molecular biology, and clinical science, combining analytical rigour and engineering capability with the ability to communicate complex findings clearly to both technical and executive stakeholders.


Key Responsibilities

  • Product ownership: Take a leading hands-on role on one of our clinical products - running the modelling work, proposing approaches and improvements, and proactively surfacing problems and solutions rather than waiting for direction.
  • Develop and improve models: Train, evaluate, and refine models across our platform - proposing architectures and training strategies, investigating underperformance, and ensuring they are optimised for specific customer requirements and real-world performance.
  • Bring research into practice: Bring advances from the literature together with your own ideas to develop effective, practical solutions.
  • Run experiments and validation studies: Design and run rigorous experiments and validation studies to test hypotheses and model performance against the high standards required for clinical use, and bring well-reasoned conclusions and recommendations on model readiness.
  • Exploratory data analysis: Conduct deep exploratory analysis on new datasets to assess feasibility, produce insights, and help drive project strategy from zero to delivery.
  • Work with data at scale: Efficiently process and handle large, high-dimensional image datasets as part of the model development workflow.
  • Cross-functional collaboration: Work closely with cross-functional teams (Product, Research, Engineering) to take models from development through to delivery.
  • Communicate results: Turn experimental and validation findings into clear conclusions and recommendations for technical colleagues and senior stakeholders, so results can inform product and clinical decisions.

Essential experience & mindset

  • One of the following backgrounds:
    • An MSc in Machine Learning, Computer Science, Mathematics, Statistics, Engineering, or a related field, with 2+ years of relevant industry experience in a fast-paced environment, ideally in a start-up.
    • A recent (or soon-to-complete) PhD in one of these fields, with some prior industry experience.
  • Ability to iterate, experiment, and deliver solutions efficiently.
  • Strong, hands-on programming experience in Python for building, training, and experimenting with machine learning models.
  • Solid, hands-on experience with a deep-learning framework (e.g. PyTorch) - building and training models, not just familiarity.
  • Experience in applying computer vision techniques to solve complex problems.
  • Deep understanding of how machine learning models work, with the ability to build and validate robust, generalisable models for real-world scenarios.
  • Familiarity with, or a strong interest in exploring, multi-modal learning and fusion models, to support the next generation of predictive modelling.
  • Ability to read recent ML research and turn it into working, tested code.
  • Proficiency in managing and processing large-scale, high-dimensional datasets, with efficient data handling within training workflows.
  • Proactive, problem-solving mindset with a sense of ownership, able to spot opportunities for improvement and help move projects forward from idea to implementation.
  • Capable of deep exploratory analysis to take a project from zero to delivery and produce insights for both technical and executive levels.
  • Knowledge of designing and running rigorous experiments as well as validation studies to prove hypotheses.
  • Adaptable and comfortable with evolving requirements and changing priorities, approaching new challenges with curiosity and openness.

Desirable / makes you stand out

  • Ability to leverage AI productivity tools (e.g., Claude Code, Gemini) to accelerate research, coding, debugging, documentation and other workflows.
  • Specific experience working with whole slide images and navigating the computational challenges associated with gigapixel-resolution pathology data.
  • Experience working in a regulated environment (e.g., Medical Devices, HealthTech) or dealing with clinical data.
  • Experience using cloud platforms (AWS/GCP) and containerisation (Docker) in day-to-day ML work.
  • Experience with Large Language Models (LLMs) and Generative AI techniques and their applications in healthcare or data synthesis.
  • Experience building models on multi-omics data (e.g. genomics, transcriptomics, proteomics), with an understanding of its practical challenges such as normalisation, batch effects, and missing modalities.
Machine Learning Engineer at Panakeia
Position posted a month 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
Alex Yeates on cord
Message Alex Yeates at Starling Bank
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