Company:
https:/www.energyjobline.com/sitemap.xml
Location: Santa Clara
Closing Date: 02/11/2024
Salary: £150 - £200 Per Annum
Hours: Full Time
Type: Permanent
Job Requirements / Description
Responsibilities:
- Develop and apply industry leading machine learning and deep learning systems to help solve business problems.
- Apply natural processing and generative AI, and customize large models for use in product applications.
- Develop and fine tune algorithms and models for time series and computer vision applications.
- Lead design and coding of big data and machine learning systems.
- Ability to translate business needs and goals into an AI approach and solution, and articulate findings to a non-technical audience.
- Design model performance metrics and retraining schedule.
- Assist with deploying models to public cloud infrastructure such as AWS and Microsoft Azure.
- Mentor other engineers, remain aware of new developments in the field, and help build and grow the team.
Qualifications:
- Bachelor's degree in computer science, mathematics, or a related field.
- 7 years of leading the design and architecture of new and existing machine learning systems.
- 5 years of experience in professional software development.
- Experience with natural processing and generative AI.
- Graduate degree in computer science, mathematics, or another quantitative field.
- 10 years of experience in model development for time series data, signal, image, and video processing.
- Deep knowledge of math, probability, statistics, and algorithms.
- Outstanding analytical and problem-solving skills.
- Prior experience in the healthcare or other regulated industries.
- Experience using the following software/tools:
- Unsupervised and supervised learning methods.
- NLP and large model frameworks such as spaCy and langchain.
- Machine learning frameworks such as Keras, PyTorch, or Tensorflow.
- Libraries such as numpy, scikit-learn, scipy and statsmodel.
- Programming: Python, .NET Core, Java.
Share this job
https:/www.energyjobline.com/sitemap.xml
Useful Links