Deep Learning Engineer

About Echobox:
We are a fast-growing, research-driven company building an artificial intelligence that helps online publishers overcome the challenges they face every day. Using novel AI, we are revolutionising the publishing industry and have a track record of building things that others have ruled out as impossible. Leading names from around the world rely on our product every day, including The Times, Le Monde, The Guardian, Vogue and many more.
Our team is our best asset. We work with extremely smart and talented individuals, who all enjoy a high degree of responsibility and independence in structuring their work.
Do you think you have what it takes to be part of Echobox? We'd love to hear from you.

About the Role:
You will report to our Head of Data Science and work closely with our Product managers, Software engineers and Data Scientists to define and execute on the future path for our products.

Key Responsibilities:
- Work closely with senior engineers and data scientists to quickly learn and apply machine learning techniques to real-world problems, shipping results fast, all whilst meeting launch deadlines.
- Take ownership of end-to-end ML model development—from data preprocessing and feature engineering to training, testing, and deployment.
- Collaborate across teams to implement machine learning solutions into production systems, ensuring that models are scalable, reliable, and effective.
- Actively contribute to refining and improving existing models and systems. If something can be optimized, you're on it—constantly looking for ways to enhance performance.
- Quickly analyze data and generate insights to drive product decisions. You’ll focus on making things work fast and efficiently, without over-complicating the process.
- Document your work and share findings clearly with the team. No jargon—just straightforward, actionable insights.
- Continuously learn new techniques and stay up to date with the latest ML trends, applying them to improve the product as you go.

Requirements:
- A degree in Computer Science, Data Science, or a related field (or equivalent practical experience).
- 2-3 years of experience in machine learning, with a strong understanding of core ML algorithms and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
- Hands-on experience with data preprocessing, feature engineering, and model training for real-world problems.
- Strong Python and Java  programming skills and familiarity with NLP algorithms and libraries.
- Solid understanding of basic statistics and how to apply it to real-world machine learning tasks.
- Familiarity with cloud platforms (AWS) and Kubernetes for deploying and scaling models.
- A passion for solving problems with data and machine learning, always looking for ways to get things done quickly and effectively.
- A proactive, results-driven mindset—eager to take ownership of tasks and deliver value without waiting for direction.
- Ability to work independently, learn fast, and iterate without being bogged down by unnecessary processes.
- Fluent written and spoken English.

Preferred Requirements:
- Experience in a fast-paced SaaS or tech environment, with an emphasis on deploying ML models to production quickly.
- Knowledge of deep learning models and frameworks, and interest in exploring cutting-edge ML techniques.
- Experience working with large datasets and distributed computing environments.
- Excellent organisational, analytical and influencing skills, with proven ability to take initiative and build strong, productive relationships.
- Experience working with cross-functional teams within a software organisation.
- Be able to easily switch between thinking creatively and analytically.
- An interest in the future of the publishing industry.

Benefits:
Our employees enjoy free breakfast every day, coffee, drinks and snacks all day, everyday. Every Monday and Friday, we order food for our weekly team lunches where everyone gets together for an hour of fun. We have regular team events (dinner, bowling, karting, poker nights, board-games etc.) for our team to get to know each other outside of work. Professionally, we host in-house conferences and an annual summer camp for all our global employees who are flown to and hosted in London. We ensure that all our employees also get pension contributions, the latest tech, generous annual leave and an amazing office with a balcony overlooking Notting Hill.