Algorithm Engineer
Xcede
3 hours ago
Contract
Not Specified
United Kingdom
Algorithm Engineer
Location: Remote IN UK O/IR35 | NL, BEL & GER B2B
Length: 6 months +
We are hiring an Algorithm Engineer to help design, build, and improve core algorithmic and data solutions within a fast-paced SaaS environment working across complex, high-volume datasets.
You will work closely with domain specialists and experienced engineers to turn business logic into reliable software solutions across forecasting, pricing, and optimisation problems. This is a hands-on engineering role with strong exposure to real production systems and excellent opportunity for technical growth.
You will collaborate across Product, Data, and Delivery teams, contributing to both day-to-day engineering delivery and the continuous improvement of platform performance and scalability.
Responsibilities
Build and improve scalable algorithms for forecasting, pricing, and optimisation across large and complex datasets
Contribute to design discussions around high-volume data processing, helping ensure reliability, explainability, and production readiness
Work closely with Product, Data, and Delivery teams to translate business requirements into practical engineering solutions
Improve the robustness, scalability, and performance of models, workflows, and distributed systems
Contribute reusable components and help raise engineering quality through code reviews, collaboration, and continuous improvement
Learn from senior engineers through pairing, reviews, and knowledge sharing while gradually taking on greater ownership
Requirements
Hands-on experience designing, developing, or deploying algorithms or data models across forecasting, pricing, optimisation, or similar analytical problem spaces
Solid Python skills and working knowledge of modern data tools such as SQL, Pandas, Polars, DuckDB, NumPy, or SciPy
Exposure to Dask, PySpark, distributed systems, or microservices is beneficial but not essential
Interest in working with large-scale or high-frequency datasets such as IoT, sensor, weather, utility, or operational data
Strong problem-solving mindset with good communication and collaboration skills
Ability to work well in cross-functional teams, ask the right questions, and communicate progress clearly
Previous SaaS experience is helpful; industry-specific domain knowledge is a plus but not require
Location: Remote IN UK O/IR35 | NL, BEL & GER B2B
Length: 6 months +
We are hiring an Algorithm Engineer to help design, build, and improve core algorithmic and data solutions within a fast-paced SaaS environment working across complex, high-volume datasets.
You will work closely with domain specialists and experienced engineers to turn business logic into reliable software solutions across forecasting, pricing, and optimisation problems. This is a hands-on engineering role with strong exposure to real production systems and excellent opportunity for technical growth.
You will collaborate across Product, Data, and Delivery teams, contributing to both day-to-day engineering delivery and the continuous improvement of platform performance and scalability.
Responsibilities
Build and improve scalable algorithms for forecasting, pricing, and optimisation across large and complex datasets
Contribute to design discussions around high-volume data processing, helping ensure reliability, explainability, and production readiness
Work closely with Product, Data, and Delivery teams to translate business requirements into practical engineering solutions
Improve the robustness, scalability, and performance of models, workflows, and distributed systems
Contribute reusable components and help raise engineering quality through code reviews, collaboration, and continuous improvement
Learn from senior engineers through pairing, reviews, and knowledge sharing while gradually taking on greater ownership
Requirements
Hands-on experience designing, developing, or deploying algorithms or data models across forecasting, pricing, optimisation, or similar analytical problem spaces
Solid Python skills and working knowledge of modern data tools such as SQL, Pandas, Polars, DuckDB, NumPy, or SciPy
Exposure to Dask, PySpark, distributed systems, or microservices is beneficial but not essential
Interest in working with large-scale or high-frequency datasets such as IoT, sensor, weather, utility, or operational data
Strong problem-solving mindset with good communication and collaboration skills
Ability to work well in cross-functional teams, ask the right questions, and communicate progress clearly
Previous SaaS experience is helpful; industry-specific domain knowledge is a plus but not require