Machine 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: 1. 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. 2. Take ownership of
end-to-end ML model development—from data preprocessing and feature
engineering to training, testing, and deployment. 3. Collaborate
across teams to implement machine learning solutions into
production systems, ensuring that models are scalable, reliable,
and effective. 4. 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. 5.
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. 6. Document your work and
share findings clearly with the team. No jargon—just
straightforward, actionable insights. 7. Continuously learn new
techniques and stay up to date with the latest ML trends, applying
them to improve the product as you go. Requirements: 1. A degree in
Computer Science, Data Science, or a related field (or equivalent
practical experience). 2. 2-3 years of experience in machine
learning, with a strong understanding of core ML algorithms and
frameworks (e.g., scikit-learn, TensorFlow, PyTorch). 3. Hands-on
experience with data preprocessing, feature engineering, and model
training for real-world problems. 4. Strong Python and Java
programming skills and familiarity with NLP algorithms and
libraries. 5. Solid understanding of basic statistics and how to
apply it to real-world machine learning tasks. 6. Familiarity with
cloud platforms (AWS) and Kubernetes for deploying and scaling
models. 7. A passion for solving problems with data and machine
learning, always looking for ways to get things done quickly and
effectively. 8. A proactive, results-driven mindset—eager to take
ownership of tasks and deliver value without waiting for direction.
9. Ability to work independently, learn fast, and iterate without
being bogged down by unnecessary processes. 10. Fluent written and
spoken English. Preferred Requirements: 1. Experience in a
fast-paced SaaS or tech environment, with an emphasis on deploying
ML models to production quickly. 2. Knowledge of deep learning
models and frameworks, and interest in exploring cutting-edge ML
techniques. 3. Experience working with large datasets and
distributed computing environments. 4. Excellent organisational,
analytical and influencing skills, with proven ability to take
initiative and build strong, productive relationships. 5.
Experience working with cross-functional teams within a software
organisation. 6. Be able to easily switch between thinking
creatively and analytically. 7. 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.
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