Sr. Machine Learning Engineer at Veritone
London, England, United Kingdom -
Full Time


Start Date

Immediate

Expiry Date

05 May, 25

Salary

0.0

Posted On

05 Feb, 25

Experience

6 year(s) or above

Remote Job

No

Telecommute

No

Sponsor Visa

No

Skills

Completion, Deep Learning, Opencv, Machine Learning, Computer Vision, Communication Skills, Software Development Tools, Pandas

Industry

Computer Software/Engineering

Description

WE ARE VERITONE

Veritone (NASDAQ: VERI) designs human-centered AI solutions. Serving customers in the talent acquisition, media, entertainment and public sector industries, Veritone’s software and services empower individuals at the world’s largest and most recognizable brands to run more efficiently, accelerate decision making and increase profitability. Veritone’s leading enterprise AI platform, aiWARE™, orchestrates an ever-growing ecosystem of machine learning models, transforming data sources into actionable intelligence. By blending human expertise with AI technology, Veritone advances human potential to help organizations solve problems and achieve more than ever before, enhancing lives everywhere. To learn more, visit Veritone.com.

POSITION SUMMARY

Our team is looking to add an ambitious Senior Machine Learning Engineer who works well in an extremely innovative and fast-paced environment. If you are capable of translating complex problems into actionable insights, then please continue reading.

MINIMUM QUALIFICATIONS:

  • PhD degree or equivalent algorithm testing and coding experiment experience in Computer Vision and Machine Learning with up-to-date extensive knowledge and experience in deep learning algorithms including the latest multimodal foundation models and generative AI frameworks’ exploration, development and implementation.
  • Extensive experience with common machine learning Python frameworks such as Tensorflow and Pytorch; and Python programming libraries such as pandas, and computer vision libraries such as OpenCV.
  • Experience in ONNX and TensorRT.
  • Very comfortable working in Linux environment.
  • Familiarity with software development tools and agile development practices.
  • 6 years experience in developing, optimizing and testing deep learning in computer vision models.
  • Excellent communication skills (written / verbal).
  • Experience in working a development team.
  • Motivated to drive tasks to completion and meeting rigorous time requirements.
  • Ability to work in a fast-paced development environment.
Responsibilities

The successful candidate will work with a team of UK (London) based developers driving the definition, development and evolution of the Veritone’s Track, which takes both images and video data and performs intelligent analysis including but not limited to object detection, tracking, recognition for law enforcement, public safety, and media entertainment applications. The work will involve developing novel deep learning models and algorithms for image and video analysis; object detection and tracking, cross-domain/cross-view object localization, person and vehicle re-identification and search, visual attribute recognition and search in videos and images, vision-language multimodal self-labelling and self-supervised learning, human-in-the-loop hard negative mining for model incremental learning, LLM (Large Language Model) driven image data generation and data distribution augmentation, uncertainty quantification for label noise minimization.

The Sr. ML Engineer is expected to:

  • Work within a multi-disciplinary software development team, although also able to work independently, and take ownership of software development tasks from specification to completion.
  • Complete developer level unit and integration testing of developed features to verify functionality and operation within limits.
  • Investigate and solve problems discovered by evaluation testing, product support and by customers and contribute to a resolution plan for each issue.
  • Provide technical input into user documentation and produce development process related technical documentation.
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