Machine Learning Engineer

Compare the Market; London; Hybrid; GBP 45,000 - 75,000; Full time

Job summary

Join a forward-thinking company as a Machine Learning Engineer, where you'll collaborate with data scientists and tech stakeholders to create automated, scalable Machine Learning products. This role involves developing and maintaining ML solutions, ensuring best practices are followed, and managing large datasets. You'll be part of a creative culture that values inclusivity and innovation, allowing you to drive your career forward. With a focus on both personal and professional growth, the company offers a range of benefits, including generous holiday allowances and private healthcare, making it a great place to thrive in your career.

Benefits

Generous holiday allowance

Private healthcare

Electric car scheme

Paid development days

Wellbeing days

CSR days

Qualifications

• Strong understanding of ML algorithms and MLOps practices.
• Proficiency in Python, SQL, R, and deep learning frameworks.

Responsibilities

• Develop and optimise integrated Machine Learning products.
• Coordinate small to medium sized machine learning projects.

Skills

Machine Learning Algorithms

MLOps Practices

Deep Learning Frameworks (TensorFlow, PyTorch)

Python

SQL

R

SQL and NoSQL Databases

Continuous Integration and Deployment

Containerization Technologies (Docker, Kubernetes)

Cloud Services (AWS, GCP, Azure)

Communication Skills

Team Collaboration

Tools

Databricks

NumPy

Pandas

Scikit-learn

Jupyter

Git

Job description

Our purpose is to make great financial decision making a breeze for everyone, and that purpose drives us every day.
It’s why we’re on a mission to create an automated quoting engine, with the simplest of experiences, wrapped in a brand everyone loves!
We change lives by making it simple to switch and save money and that’s why good things happen when you meerkat.

We’d love you to be part of our journey.
As a Machine Learning Engineer, you will be working closely with data scientists and a wide range of business and tech stakeholders with varying levels of understanding towards Machine Learning, and will identify the tech requirements to productionise automated, scalable and stable Machine Learning products integrated into production systems that deliver actions and/or actionable insights.

Everyone is welcome.
We have a culture of creativity. We approach our work passionately, improve constantly and celebrate our wins at every turn. We are an inclusive workplace and our employees are comfortable bringing their authentic, whole selves to work. This means we’re excited to hear from people with a range of skills, experiences and ideas. We don’t expect you to tick all the boxes, but would love to hear what makes you great for this role.

Some of the great things you’ll be doing:

1. Develop, maintain, monitor (health & performance) and optimise integrated Machine Learning products.
2. Work closely with Data Engineering, Platform and Architecture teams to improve and develop new products, integrations, tools and technologies.
3. Work with data scientists to productionise various ML models, ensuring the code follows best practices; is effective, scalable and conforms to CTMs Engineering & Tech standards.
4. Follow best practices for the management and interrogation of large scale ‘structured’ and ‘unstructured’ datasets (million+ rows with thousand+ features, policy documents, etc).
5. Enable the collection of new data and the refinement of existing data sources.
6. Help manage day to day operations of the Data Science & Analytics platform (Databricks), and other ML Solutions built & operated tech across various platforms.
7. Coordinate and manage small to medium sized machine learning projects in small cross functional squads.

What we’d like to see from you:

1. Strong understanding of a wide range of ML algorithms.
2. Understanding of MLOps practices for managing and monitoring models in production.
3. Experience with deep learning frameworks (e.g. TensorFlow, PyTorch).
4. Proficiency in programming languages such as Python, SQL and R.
5. Knowledge of SQL and NoSQL databases for data storage and retrieval.
6. Experience with LLM application design and deployment.
7. Strong software engineering skills, including version control (Git), code reviews, and unit testing.
8. Familiarity with common data science libraries and tools (e.g., NumPy, Pandas, Scikit-learn, Jupyter).
9. Experience in setting up and managing continuous integration and continuous deployment pipelines.
10. Proficiency with containerization technologies (e.g., Docker, Kubernetes).
11. Experience with cloud services (e.g., AWS, GCP, Azure) for model deployment and data management.
12. Strong verbal and written communication skills for both technical and non-technical audiences.
13. A strong team player with the ability to collaborate effectively and contribute to peer reviews within the team.

There’s something for everyone.
We’re a place of opportunity. You’ll have the tools and autonomy to drive your own career, supported by a team of amazingly talented people.
And then there’s our benefits. For us, it’s not just about a competitive salary and hybrid working, we care about what matters to you. From a generous holiday allowance and private healthcare to an electric car scheme and paid development, wellbeing and CSR days, we’ve pretty much got you covered!