Machine Learning Engineer (Python, Algorithmic Trading, Stats)

Machine Learning Engineer (Python, Algorithmic Trading, Stats)

  • Location

    Cambridge, Cambridgeshire

  • Sector:

    Machine Learning & AI

  • Job type:


  • Salary:

    £60000 - £100000 per annum + equity and bens

  • Contact:

    Anna Heneghan

  • Email:


  • Job ref:


  • Published:

    2 months ago

  • Expiry date:


  • Startdate:


  • Consultant:


Machine Learning Engineer (Python, Algorithmic Trading, Stats)

We are currently looking for a passionate Machine Learning Engineer (Python, Algorithmic Trading, Stats) to join a tier-one start-up organisation based in Cambridge, currently using their unique Machine Learning to tackle algorithmic trading. You will be part of the development process, from the data processing all the way through to the deployment of the model.

As a Machine Learning Engineer, you will be part of an agile environment and small team, with continual exposure to AI technology. You will be working with raw and real life datasets, detecting the faults and missing data. From there, you will gaining insights through predictive models, and supervised learning techniques.

We're looking for a Machine Learning Engineer, who is willing to take on a hands-on approach and join a team of researchers and engineers who are paving the way in regards to AI decision making. Within this organization, you will be working with Python and Tensorflow and implementing your previous experience.

What we can offer a Machine Learning Engineer (Python, Algorithmic Trading, Stats):

  • Work for recognised leaders within Machine Learning
  • Strong salary and package
  • Flexible working environment, start-up environment
  • Remain part of the academic field

Key Skills: Machine Learning Engineer (Python, Algorithmic Trading, Stats); Tensorflow, C++, C, Java, Python, C#, Distributed Algorithms. Distributed systems, BSc, MSc, MPhil, PhD, Post-Doc, Research, R&D, startup, Multithreading. Machine Learning, AI, Artificial Intelligence, NLP, Natural Language Processing, Linguistics, Computational Biology, Computational Linguistics, Reinforcement Learning, Multi-Agent Systems, Deep Learning, Bayesian Inference, Probabilistic Models