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Engineer – ML Technology

Tech-Driven Global Hedge Fund


New Listing

The Team

Machine Learning Technology is a small and agile team that facilitates the use of machine learning tools across the firm, with a particular focus on generative AI. Alongside developing and provisioning the platform, you’ll also consult with teams throughout the business assisting them in transforming their concepts into high-impact solutions.

As an engineer in the ML Technology team, you’ll help to develop a cutting-edge platform, collaborating closely with company-wide teams and individuals to deeply understand their needs and guide them in leveraging the platform. Where required, you will also use both the platform and your expertise to design and implement bespoke solutions to meet their requirements.

Positioned at the crossroads of finance and the burgeoning field of AI engineering, the Machine Learning Technology team exists in a rapidly progressing space. This team provides an opportunity to make significant contributions across the business, developing solutions to problems that were very recently considered to be either impossible or extremely difficult to solve.

The Technology

Core systems are almost all running on Linux and most of the code is in Python, with the full scientific stack: numpy, scipy, pandas, scikit-learn to name a few of the libraries used extensively. For storage, they rely heavily on MongoDB. They use Docker, Kubernetes and Airflow to streamline deployments and leverage OpenFin and React for front-end development.

Because of the small team size and the dynamic nature of the business, technology choices are not static and team members can explore new technologies freely. This means you will be able to shape the technology landscape and have a high impact early on.

Working Here

This fund has a small company, no-attitude feel. It is flat structured, open, transparent and collaborative, and you will have plenty of opportunity to have enormous impact on the firm. They are actively engaged with the broader technology community.

  • They host and sponsor London’s PyData & Machine Learning Meetups and open-source some of their technology
  • They regularly talk at leading industry conferences, and tweet about relevant technology and how they’re using it.

They have a fantastic open-plan office overlooking the River Thames, and continually strive to make the environment a great place in which to work.

  • Regular social events; from photography to climbing, karting, wine tasting and monthly team lunches
  • Annual away days and off-sites for the whole team
  • Canteen with a daily allowance for breakfast and lunch, and an on-site bar for in the evening
  • As well as PCs and Macs, you’ll find loads of cool tech including light cubes and 3D printers, guitars, ping-pong and table-football, and a piano.

Technology and Business Skills


  • Substantial quant development engineering experience
  • Excellent team management and communication skills
  • A knowledge of a modern data-science stack
  • Demonstrable programming experience, ideally in Python, Java, (C++ desirable)
  • Experience of the challenges of dealing with large data sets, both structured and unstructured
  • Used a range of open source frameworks and development tools, e.g. NumPy/SciPy/Pandas, Spark, Kafka, Flink
  • Working knowledge of one or more relevant database technologies, e.g. Oracle, Postgres, MongoDB, ArcticDB.
  • Proficient on Linux


  • An excellent understanding of financial markets and instruments
  • An understanding of quantitative portfolio allocation approaches
  • Prior experience of working with financial market data
  • Experience of web based development and visualisation technology for portraying large and complex data sets and relationships
  • Relevant mathematical knowledge, e.g. statistics, time-series analysis.

Personal Attributes:

  • Strong academic record and a degree with high mathematical and computing content e.g. Computer Science, Mathematics, Engineering or Physics from a leading university
  • Craftsman-like approach to building software; takes pride in engineering excellence and instils these values in others
  • Demonstrable passion for technology e.g. personal projects, open-source involvement
  • Intellectually robust with a keenly analytic approach to problem solving
  • Self-organised with the ability to effectively manage time across multiple projects and with competing business demands and priorities
  • Excellent interpersonal skills; able to establish and maintain a close working relationship with traders, quantitative researchers, and senior business people alike
  • Confident communicator; able to argue a point concisely and deal positively with conflicting views.

Work-Life Balance and Benefits

Proud to provide the best working environment possible for all of its employees, they are committed to equality of opportunity. They believe that a diverse workforce is a critical factor in the success of the business, and this is embedded in the culture and values. Running a number of external and internal initiatives, partnerships and programmes which help them to attract and develop talent from diverse backgrounds and encourage diversity and inclusion; they’re also a Signatory of the Women in Finance Charter.

They offer comprehensive, firm-wide employee benefits, including competitive holiday entitlements, pension/401k, life and long-term disability coverage, group sick pay, enhanced parental leave and long-service leave. Additional benefits are tailored to local markets and may include private medical coverage, discounted gym membership and wellbeing programmes.