Hiscox on cord

Hiscox

Machine Learning Engineer

External position
York, UK
Hiring internally for Hiscox?
Insurance
Specialist insurer since 1901
Posted
2 months ago
Checked
cord regularly checks that external positions are still open
3 days ago

Skills & Experience

Job roles: Machine Learning Engineer
Experience level: Mid, Senior
Core skills considered: Python, Flask, FastAPI, Agile, CI/CD
Other skills considered: Docker, Terraform, AWS, GCP, Software Architecture

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

We are looking for an experienced machine learning engineer to join a newly formed ML Engineering team. As a Machine Learning Engineer at Hiscox, you will play a key role in building and maintaining the infrastructure to acquire data from the data platform, deploy models, maintain, monitor and upgrade core data science services in both Azure and GCP that supports the deployment of machine learning models across the enterprise. You'll work closely with Data Scientists, Platform Engineers, and Developers to ensure seamless integration and scalable, production grade machine learning solutions.

This is a hands-on engineering role focused on developing APIs, infrastructure, and deployment pipelines for machine learning models. You'll be expected to write clean, reusable code, follow best practices in cloud and software engineering, and contribute to the operational excellence of our machine learning systems.

In addition to strong engineering skills, you'll bring a solid understanding of Data Science principles. You should be comfortable reading, questioning, and interpreting machine learning models to ensure they are deployed appropriately and effectively. Your ability to bridge the gap between model development and production deployment will be key to delivering robust, high impact machine learning solutions. You'll be expected to understand and implement methodologies from the ML OPs life cycle.

You'll also be expected to work in an Agile environment, contributing to iterative development cycles, collaborating across disciplines, and adapting quickly to changing requirements.


Key Responsibilities

  • Develop and maintain infrastructure for deploying ML models in both real-time and batch environments.
  • Build and maintain Python APIs (Flask/FastAPI) to serve ML models.
  • Collaborate with cross discipline engineers to integrate ML services into user-facing applications.
  • Work with platform engineers to align with infrastructure best practices and ensure scalable deployments.
  • Review pull requests and contribute to code quality across the MLE team.
  • Monitor and maintain cloud-based ML services, ensuring reliability and performance.
  • Design and implement CI/CD pipelines for ML model deployment.
  • Write unit tests and follow object-oriented programming principles to ensure maintainable code.
  • Support data modelling and cloud networking tasks as needed.
  • Contribute to the development and improvement to our model registry, including tracking and implementation of model discontinuation upgrades and model monitoring.
  • Ownership of the deployment framework for all data science services. You will have oversight of how data will flow into the data science life cycle from the wider business data warehouse.
  • Oversight of the automation of the data science life cycle (dataset build, training, evaluation, deployment, monitoring) when we move to production.
  • Interest and ability to work closely with a team and collaborate on all aspects of the data science and deployment lifecycle.
  • Work collaboratively with data scientists, data engineers and other technical teams in order to help support maturation of analytics practice within the organization.
  • Writing high quality python code using industry best practice for model training and deployment.

Person Specification

  • Bachelor's/Master's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering) or equivalent.
  • 3-5 years as an ML engineer.
  • Good understanding of core data science principles and understanding of challenges of migrating research code into production code.
  • Hands on experience in machine learning engineering, including deploying, monitoring, and maintaining ML models in production environments (Neural networks, Random forests etc.).
  • Experience in financial services or insurance is an advantage but not required.
  • Solid experience as a Python developer, ideally in a machine learning engineering context (Flask/FastAPI, OOP, unit testing).
  • Strong understanding of software engineering best practice.
  • Experience with TDD.
  • Experience with infrastructure as code tools like Terraform or similar Infrastructure as Code (IaC) tools.
  • Hands on experience with cloud platforms (GCP, AWS, or Azure).
  • Familiarity with containerization using Docker and orchestration of deployments.
  • Experience with CI/CD tools and Git-based development workflows.
  • Understanding of API operations monitoring and logging.
  • Strong problem-solving skills and ability to work independently on technical tasks.
  • Familiarity with Agile methodologies and experience working in Agile teams.
Machine Learning Engineer at Hiscox
Position posted 2 months 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
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