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Founding Machine Learning Engineer - AI Start-Up - Hybrid - Equity Ownership

Opus Recruitment Solutions
Posted 18 days ago, valid for 9 days
Location

London, Greater London SW1A2DX, England

Salary

£130,000 per annum

Contract type

Full Time

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Sonic Summary

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  • The position is for a Founding Machine Learning Engineer at a fast-growing AI start-up, offering equity ownership.
  • Candidates must have an advanced degree in a relevant field and over 5 years of experience in machine learning or applied research.
  • Key responsibilities include leading the integration of systems that manage interactions between AI models and human operators.
  • Proficiency in Python and modern ML frameworks, along with a strong understanding of data structures and algorithms, is required.
  • The salary for this role is competitive, reflecting the candidate's expertise and experience in the field.
Founding Machine Learning Engineer
Hybrid Working
Exciting Start-up AI Company

The Opportunity:
You will be joining the founding team with equity ownership in a fast growing AI start-up and will be instrumental in defining the future of AI orchestration. You will lead the creation and integration of advanced systems that seamlessly manage interactions between AI models, cutting-edge tools, and human operators.

Required Qualifications:
  • Educational Background: Advanced degree (Master's/PhD) in Computer Science, Machine Learning, Data Science, or a related field.
  • Specialized Expertise: Expertise in LLM frameworks, agent building, and prompt engineering.
  • Professional Experience: Over 5 years of experience in machine learning or applied research.
  • Technical Knowledge: Strong understanding of data structures, algorithms, and software engineering principles.
  • Proven Capability: Demonstrated success in deploying production-ready ML systems.
  • Programming Skills: Proficiency in Python and modern ML frameworks.
  • Systems Experience: Hands-on experience with distributed systems and microservices architecture.

Desirable Skills:
  • Cloud: AWS/GCP/Azure
  • Deep Learning Frameworks: Experience with PyTorch and TensorFlow.
  • Graph Databases: Knowledge of graph databases and knowledge graphs.

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