Senior ML Engineer - Performance Platform Intelligence
Full-time
London, United Kingdom • In office | Hybrid | Remote (UK only)
About GoGorilla
GoGorilla is the world's first performance marketing company built on financial technology. We've engineered a platform that hardwires client objectives into every campaign, ensuring transparent, auditable results that traditional agencies can't match. When our clients win, you win. You'll join a high-performance London team where your commercial impact directly shapes your career trajectory and financial rewards.
About the role
As a Senior ML Engineer, you will be a key architect of our performance platform intelligence. You will be responsible for designing, building, and deploying the machine learning models that power our predictive analytics and decision-making. This is a highly technical and strategic role that offers the opportunity to work on a unique and complex set of problems at the intersection of machine learning, software engineering, and marketing science.
Day to day, you'll be working with large datasets, building machine learning models, and deploying them to production. This role requires a deep understanding of machine learning principles, a passion for building scalable systems, and a desire to build a world-class machine learning platform.
Working pattern and flexibility
This is a senior role with a high degree of flexibility. You can choose to work from our central London office, adopt a hybrid approach, or work fully remotely from anywhere in the UK. We trust you to manage your own time and deliver against your objectives. Time tracking is required for remote work to ensure security and progress monitoring, which is an industry-standard practice.
Leadership trajectory
This is a senior role with a clear path to technical leadership. You'll start by mastering our machine learning stack and consistently delivering high-impact models, with the opportunity to progress to a Lead or Principal role within 18 to 24 months. Exceptional performers will have the chance to build and lead their own machine learning team.
What you will be doing
Design, build, and deploy machine learning models that power our predictive analytics and decision-making.
Work with large datasets from a variety of sources, including our internal systems, third-party APIs, and client data.
Build and maintain our machine learning infrastructure, including our data pipelines, model training and deployment systems, and monitoring and alerting tools.
Collaborate with our data scientists, analysts, and engineers to understand their needs and build solutions that meet them.
Stay up-to-date on the latest trends and techniques in machine learning and MLOps.
What you will bring
A strong background in machine learning or a related field.
Expertise in machine learning, with a deep understanding of techniques like deep learning, reinforcement learning, and natural language processing.
Proficiency in Python and experience with machine learning libraries like TensorFlow, PyTorch, and scikit-learn.
Experience with MLOps tools and technologies, such as Kubeflow, MLflow, and Docker.
Right to work in the UK. We do not offer visa sponsorship.
A willingness to learn and a coachable mindset.
You should not apply if
You are not passionate about machine learning and building world-class machine learning platforms.
You are not a creative problem-solver who enjoys tackling complex and ambiguous challenges.
You are not a team player who is willing to collaborate with others to achieve common goals.
You are not interested in a role that requires continuous learning and improvement.
You are not comfortable with a role that has a high degree of accountability for the performance and reliability of our machine learning models.
How we work
Outcomes first – your success is measured by the impact your models have on our business and our clients.
Autonomy with accountability – you have the freedom to manage your own development process with clear expectations for results.
Build the playbook – you will contribute to our machine learning playbook by developing and refining our model development and deployment process and best practices.
Be the expert – you will be the go-to person for all things related to our performance platform intelligence.
Continuous improvement – feedback and data-driven insights shape our model development process and drive continuous innovation.
Compensation and progression
Base salary: £70,000 to £90,000 (London), with adjustments for other UK locations (£60,000 to £80,000).
On-target performance bonus: Significant performance bonuses and success-sharing opportunities.
Company profit-sharing: Participation in overall company success.
Equity: A substantial equity package reflecting the seniority and strategic importance of this role. Meaningful equity participation is a core part of our compensation philosophy for high-performing team members, offering a stake in our long-term success.
Benefits: Private healthcare for full-time UK employees after 6 months probation, 25 days holiday plus bank holidays, laptop and modern tools, learning budget and regular team events.
Progression: Clear path to Lead or Principal role within 18-24 months, with opportunities to build and lead your own machine learning team.
30-60-90 day expectations
Day 30 – complete onboarding, learn our machine learning stack, and begin exploring our data.
Day 60 – take ownership of your first machine learning project and begin contributing to our machine learning playbook.
Day 90 – consistently delivering high-impact models and demonstrating a clear impact on our business.
Our hiring process
We keep the steps simple so you can demonstrate how your skills drive outcomes and align with our culture. For this role, the journey usually follows our standard path – application, a short cultural profile, a light role task if applicable, interviews, offer and onboarding. See the careers page for specifics.
Typical flow for this role
Application – submit your CV and a short note on your experience with machine learning.
Cultural assessment – brief values and collaboration profile, plus short video questions.
Role task – a machine learning challenge to assess your skills and creative thinking.
Interviews – meet the hiring lead and other members of the data and engineering teams.
Offer and checks – written offer with base, bonus, and equity structure, right-to-work and references.
Onboarding – a clear plan, team introductions and access to all company resources.
Important notes for candidates
We do not use third-party recruitment agencies. Do not send CVs through agencies.
Apply only through our official channels. We will never ask for payment or personal financial information during the hiring process.
Double-check sender domains in email communications.
By applying, you confirm that the information is accurate and understand that employment is subject to right-to-work checks and references.
We process candidate data in line with our privacy notice.
