- Developing end to end ML training pipelines
- Incorporate ML models in software products
- Optimizing ML training and validation pipelines
- Handling hardware (GPU) deployment issues
- Excellent Python and software engineering skills.
- Experience of using and developing MLOps tools in a challenging production environment.
- Knowledge or Experience working with C++ and GPU for optimisation would be beneficial.
Company
Location
Worcester, England - United Kingdom
Job type
Full-Time
Python Job Details
Reqiva have partnered with an award winning company who are world leaders in Motion Capture, high performance software and hardware products across multiple sectors.
They are looking for an MLOps (Machine Learning) engineer who would help in shaping and solving complex and exciting challenges within the computer vision and motion capture.
This company are based in Oxford with the opportunity for remote working, with an open office for local candidates but also happy with candidates commuting to their office every 2 - 4 weeks.
Our client are looking to ideally bring on a candidate within the salary range of £55,000 - £75,000 per annum (D.O.E) but also offer private medical care as well as a 10% pension.
Responsibilities
They are looking for an MLOps (Machine Learning) engineer who would help in shaping and solving complex and exciting challenges within the computer vision and motion capture.
This company are based in Oxford with the opportunity for remote working, with an open office for local candidates but also happy with candidates commuting to their office every 2 - 4 weeks.
Our client are looking to ideally bring on a candidate within the salary range of £55,000 - £75,000 per annum (D.O.E) but also offer private medical care as well as a 10% pension.
Responsibilities
If you feel this role would be suitable based on the requirements then don't hesitate to apply for consideration for this role and for someone to contact you!
Email - [email protected]
Mobile - 01189595552
Email - [email protected]
Mobile - 01189595552
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