Machine Learning Engineer

Machine Learning Engineer

Posted 5 days ago by Templeton & Partners - Innovative & Inclusive Hiring Solutions

Negotiable
Undetermined
Undetermined
London Area, United Kingdom

Summary: The Machine Learning Engineer role involves creating scalable ML tooling and infrastructure to support research scientists, emphasizing collaboration and efficient problem-solving. The position requires writing maintainable code and coordinating with various internal teams to integrate existing systems. Candidates should have a strong background in deep learning frameworks and experience with large data sets. The role is focused on backfilling a position that emphasizes efficient infrastructure and ML frameworks.

Key Responsibilities:

  • Create robust, flexible and scalable ML tooling and infrastructure.
  • Work collaboratively as part of a multifunctional team.
  • Write clean, maintainable code and debug complex problems.
  • Coordinate with internal infrastructure and tool teams.
  • Learn constantly and embrace ambiguity in problem-solving.

Key Skills:

  • Bachelor's degree in Computer Science or related field, or equivalent work experience.
  • 4+ years industry experience with deep learning frameworks in Python, such as Pytorch or Tensorflow.
  • 2+ years industry experience working with large, complex data sets for machine learning.
  • Experience implementing and evaluating end-to-end prototypical learning systems.
  • Deployment and continuous integration experience.

Salary (Rate): undetermined

City: London Area

Country: United Kingdom

Working Arrangements: undetermined

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT

Detailed Description From Employer:

Job Description:

  • Responsibilities:
    • Create robust, flexible and scalable ML tooling and infrastructure which supports research scientists to leverage company's powerful infrastructure (through e.g. source control, distributed compute clusters, data storage)
    • Work collaboratively as part of a multifunctional team where communication, documentation and teamwork are highly valued
    • Write clean, maintainable code, debug complex problems that span systems, prioritize ruthlessly and get things done with a high level of efficiency
    • Coordinate with a large set of internal infrastructure and tool teams across the lab and across the company to evaluate and integrate with existing systems
    • Learn constantly, dive into new areas with unfamiliar technologies, and embrace the ambiguity of AR/VR problem solving
  • Requirements:
    • Bachelor's degree in Computer Science or related field, or equivalent work experience.
    • 4+ years industry experience with deep learning frameworks in Python, such as Pytorch or Tensorflow.
    • 2+ years industry experience working with large, complex data sets for machine learning, including capture and annotation.
    • Demonstrated experience implementing and evaluating working and end-to-end prototypical learning systems.
    • Experience working with high performance or distributed compute solutions.
    • Deployment and continuous integration experience.
  • Preferred Qualifications:
    • Familiarity with Machine Learning for Audio, multimodal or DSP purposes
    • Experience writing scalable ML tooling/pipelines for use by researchers
    • Experience in Linux or Windows shell scripting
    • Ability to gather requirements and work closely with researchers to develop novel solutions
    • History of writing code to support the execution of research initiatives
  • Top 3 must-have HARD skills:
    • We're looking for Python and infrastructure focused software engineers
    • PyTorch or similar AI/ML engines
    • Distributed infrastructure
  • Good to have skills:
    • Working with complex, real-world multimodal data
    • Audio
    • Collaboration with research users/customers to deliver robust and stable tooling to address their needs
  • How many years of experience should they have?
    • 4+ years of industry experience writing Python / ML code
  • What is the Story Behind the Need?
    • Backfilling a role for an ML pipeline-focussed software engineer, focussing on efficient and scalable infrastructure, and ML frameworks and tooling