This website uses cookies. Read our cookie policy for more information. By continuing to browse this site you are agreeing to our use of cookies.

hidden og tag linkedin

Lead Machine Learning Engineer – Global DS Consultancy, London, UK

Job Type:
Permanent
Job Sector:
Data, Technology
Job Category:
Development, Data Science & Data Engineering
Country:
UK
Area:
London
Location:
London
Salary:
90,000 to 120,000 per annum
Salary Description:
benefits, bonus
Job Ref:
HQ00025444

Lead Machine Learning Engineer – Global DS Consultancy

Xcede's Data Science & Engineering team are currently working with one of the world’s most respected Data Science consultancies on a high-profile role. Their clients range wildly from the most prominent names in banking / fintech through to leading media and sports outlets. With a very impressive Data Science, and Data Infrastructure Engineering, and Machine Learning Engineering team in place already, the company are looking to expand the depth of their knowledge in the latter by hiring another Lead Machine Learning Engineer

Key Responsibilities:

- You’ll work very closely with the company’s Data Science team to help productionise / deploy their algorithms.
- You’ll be a key mentor figure to the seven other ML Engineers in the unit.
- Lead the charge in expanding the unit – our client is continuing to scale the team based on the huge demand they’re experiencing.

Requirements:

- A relevant MSc / BSc in Computer Science, Distributed Systems, Maths, or a related area.
- Excellent programming skills – particularly in Scala, Java, Python
- Some experience working in a distributed processing environment e.g. Hadoop, Spark
- Experience working in in an environment that values testing, pair programming, etc.
- Data manipulation skills (SQL, Postgres, etc)
- A deep understanding of a variety of ML algorithms
- Team lead / mentoring experience.

If you are interested in this or other Data Scientist or Data Engineer positions, please contact Niall Wharton on niall.wharton@xcede.co.uk or +44(0)203 301 9908

Contact Details:
Tel: 0203 301 9908
Fax: 0203 301 9901
Contact: Niall Wharton

You may return to your current search results by clicking here.

Latest Job Listings