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Machine Learning Engineer at Rezatec

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  • Didcot
  • fulltime

(Full or Part Time, with flexibility as to working hours and location)

We are Rezatec, a global specialist geospatial AI company providing landscape intelligence.

Rezatec has an incredibly exciting journey ahead, with ambitious goals to expand our global customer base and develop new solutions. Our success is driven by our people. And we are keen to talk to talented individuals who are excited about developing one of the coolest technology platforms on the planet.

Our powerful analytics platform fuses Artificial Intelligence with leading-edge satellite data, to look at the physical and environmental hazards that threaten asset integrity. We exist to help our customers prioritise investment, optimise resources and maximise the value of their assets in new ways

Founded in 2012, we have grown our customer base across multiple industry sectors including Forestry, Water, Agriculture and Energy

In 2013 we were awarded the ‘Climate KIC award’ and in 2018 we received ‘The Most Innovative Technology Award’ at Utility Week Live.

We are backed by Gresham House Ventures, Claret Capital Partners, Caphaven Partners, and Run Capital Investment. Our tech partners include Binnies, MeterSYS, Forsite and ISOIL Industria.


About You

Reporting to the Team Lead Geospatial Engineer, the Machine Learning Engineer is responsible for transforming our machine learning ideas into deployed applications to help us deliver our product led vision and shape the business of the future.

You will be collaborating with our Technical Head of Data Science, Data Engineering and Product teams, as well as other parts of the business to create industry-leading products that are robust, reliable and scalable through the leveraging of new and creative data-sources. You will use your expertise and continual improvement mindset to employ the latest in AI thinking and application of machine learning within the portfolio’s creation. This will be particularly critical as we scale up our operations and strive to deliver higher quality data to a larger number of customers.

Working as part of a matrix pod structure, you’ll thrive in an environment of clear, continuous communication and collaboration and you’ll be able to successfully manage multiple priorities in a dynamic agile setting. You’ll embrace change, seeking opportunities through curiosity and demonstrate a growth mindset.


What you will be doing

  • Develop robust methods for standardising and deploying machine learning products, via experimentation and testing
  • Design and develop new machine learning workflows/products from initial prototype through to productised application, working with key stakeholders to deliver solutions that meet customer requirements
  • Constructively review and seek out feedback on implemented methods to capture learnings and improve for the future
  • Proactively suggest improvements to existing processes
  • Provide insight on the feasibility of ideas to ensure that the best quality products are created, in the simplest way possible
  • Provide insight and support to the rest of the company on Machine Learning engineering topics
  • Working closely with the Data Science Team to ensure work produced is of meets the standards for deployment and ver
  • Helping to build and maintain the data warehouse capability ensuring the inputs, products and models can be easily retrieved and used as a trusted source to build out Rezatec’s portfolio and capabilities


  • Proven track record of both the understanding and application of machine learning techniques and algorithms in a commercial setting (Regressions, Decision Trees, Random Forest, SVM, NNs) with an advance Level of Python (R desirable)
  • Ability to evaluate statistical and ML models keeping in mind performance, accuracy, robustness, maintainability, and quality
  • Experience using SQL and accessing APIs in a language of choice
  • Understanding of database design best practices
  • Experience of building and maintaining ML pipelines, algorithms, and applications
  • Familiarity with machine learning frameworks (like TensorFlow or PyTorch) and libraries (like scikit-learn)
  • Experience with Git-based version control systems
  • Comfortable working with complex and incomplete datasets
  • Experience with common software containerization tools (e.g. Docker, Kubernetes)
  • Experience developing data pipelines with workflow orchestrations tools (e.g. Prefect, Apache Airflow)
  • Experience working with geospatial data, both raster and vector
  • Experience with CI/CD tools
  • Experience of working in a fast moving, high growth business would be advantageous


As well as all the usual things you’d expect, we’ve highlighted what we feel makes us stand out from the crowd!

  • Ongoing remote and flexible working – we'll consider any pattern of hours if it can work for your role, with a focus on achieving a healthy Work-Life balance
  • Share options for all employees
  • Pension
  • 30 days holiday, plus public holidays
  • Private Medical Insurance
  • Learning and Development
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