Job Specifications
Work where work matters.
Elevate your career at Qodea, where innovation isn't just a buzzword, it's in our DNA.
We are a global technology group built for what's next, offering high calibre professionals the platform for high stakes work, the kind of work that defines an entire career. When you join us, you're not just taking on projects, you're solving problems that don't even have answers yet.
You will join the exclusive roster of talent that global leaders, including Google, Snap, Diageo, PayPal, and Jaguar Land Rover call when deadlines seem impossible, when others have already tried and failed, and when the solution absolutely has to work.
Forget routine consultancy. You will operate where technology, design, and human behaviour meet to deliver tangible outcomes, fast. This is work that leaves a mark, work you'll be proud to tell your friends about.
Qodea is built for what's next. An environment where your skills will evolve at the frontier of innovation and AI, ensuring continuous growth and development.
We are looking for a Senior Machine Learning Engineer to be responsible for the end-to-end lifecycle of machine learning models that power core product features. You will design, build, and deploy innovative ML solutions, directly impacting the user experience through personalization, recommendations, and intelligent systems.
We look for people who embody:
Innovation to solve the hardest problems.
Accountability for every result.
Integrity always.
About The Role
Lead the algorithm selection, design, and prototyping of machine learning models to solve complex business problems, including recommendation, personalization, and predictive analytics
Apply your expertise in statistical modeling and machine learning to perform deep data analysis, guide crucial feature selection, and identify opportunities for product improvement
Own the full ML lifecycle, from breaking down discrete steps of a pipeline (e.g., with a DAG) to analyzing model implementations and improving their robustness in the wild
Implement and manage robust model observability, tuning, and optimization processes to ensure sustained performance and accuracy post-deployment
Develop and maintain data pipelines to process and prepare data for model training and evaluation
Design and conduct A/B tests to evaluate model performance and its impact on key business metrics
Collaborate closely with product managers and engineers to define problems and deliver effective AI-driven solutions
Mentor other team members, champion best practices in machine learning engineering, and stay current with the latest advancements in the field
This role is designed for impact, and we believe our best work happens when we connect. While we operate a flexible model, we expect you to spend time on site (at our offices or a client location) for collaboration sessions, customer meetings, and internal workshops.
Requirements
What Success Looks Like
Hands-on experience designing and deploying production-grade machine learning systems
Strong foundational knowledge of various machine learning algorithms and a proven ability to select the appropriate methodology, avoiding a one-size-fits-all approach
Proven experience in areas such as recommendation systems, personalization, natural language processing (NLP), or semantic search
Expert-level programming skills in Python, with deep, hands-on experience using data science and ML libraries such as Pandas, Scikit-learn, TensorFlow, or PyTorch
Experience with data storage technologies (e.g., SQL, NoSQL, Key-value) and their scaling characteristics
Experience with large-scale data processing technologies (e.g., Spark, Beam, Flink) and associated patterns (Batch vs. Stream), with a deep understanding of when to use them
Experience using cloud platforms (e.g., GCP) at scale
Experience deploying ML-based solutions at scale using cloud-native services
Excellent communication and collaboration skills, with the ability to thrive in a fast-paced, cross-functional team environment
Benefits
We believe in supporting our team members both professionally and personally. Here's how we invest in you:
Compensation and Financial Wellbeing
Competitive base salary
Matching pension scheme (up to 5%) from day one
Discretionary company bonus scheme
4 x annual salary Death in Service coverage from day one
Employee referral scheme
Tech Scheme
Health and Wellness
Private medical insurance from day one
Optical and dental cash back scheme
Help@Hand app: access to remote GPs, second opinions, mental health support, and physiotherapy
EAP service
Cycle to Work scheme
Work-Life Balance and Growth
36 days annual leave (inclusive of bank holidays)
An extra paid day off for your birthday
Ten paid learning days per year
Flexible working hours
Market-leading parental leave
Sabbatical leave (after five years)
Work from anywhere (up to 3 weeks per year)
Industry-recognised training and certifications
Bonusly employee recognition and reward