Algorithm Engineer
Posted Today by Jobserve
Negotiable
Inside
Remote
Remote work
Summary: The Algorithm Engineer role involves designing, building, and enhancing algorithmic and data solutions in a fast-paced SaaS environment, focusing on complex datasets. The position requires collaboration with domain specialists and engineers to develop reliable software solutions for forecasting, pricing, and optimization. This hands-on role offers significant exposure to production systems and opportunities for technical growth. The engineer will contribute to both engineering delivery and the improvement of platform performance and scalability.
Key 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
Key Skills:
- 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 required
Salary (Rate): undetermined
City: undetermined
Country: UK
Working Arrangements: remote
IR35 Status: inside IR35
Seniority Level: undetermined
Industry: IT
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