ML Engineer | Code Monk

June 3, 2024
Application ends: July 31, 2024
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Deadline date:
July 31, 2024

Job Description

What You’ll Do

  • Create hypotheses, design experiments, and collect results for machine learning model improvement.
  • Design, build, and maintain machine learning models with an emphasis on LLMs, knowledge distillation, and scalability.
  • Collaborate to push the boundaries of machine learning creating Small Language Models and using knowledge distillation
  • Implement best practices and design to ensure high-quality software development including coding, code reviews, testing, and maintenance
  • Engage in continuous learning to keep abreast of the latest machine learning
  • Frameworks and methodologies for domain-specific applications.
  • Work closely with the founders and early customers to understand pain points and build solutions to support growth strategies
  • Conduct research and experimentation to explore new techniques, algorithms, and technologies that can drive innovation and competitive advantage.
  • Collect, clean, pre-process, and analyse large datasets to extract meaningful insights and features for model training and evaluation.
  • Document methodologies, processes, and findings. Communicate results and insights effectively to technical and non-technical stakeholders
  • Collaborate with cross-functional teams to integrate ML models into cloud-based infrastructure and full-stack development projects.

Preferred experience

  • Exceptional foundation and previous work experience with machine learning algorithms, frameworks, and libraries. With a particular focus on any of the following: ANNs, XGBoost, Large
  • Language Models and Natural Language Processing.
  • Computer science background in software development practices (git, peer review) and programming languages relevant to machine learning such as Python
  • An understanding of cloud infrastructure and full-stack development to support end-to-end machine learning model deployment.
  • Working with Google AI products such as VertexAI;

Bonus Experience

  • Proven track record of implementing ANNs and/or Large Language Models (LLMs) within enterprise environments
  • Experience working at deep tech companies involved in developing novel intellectual property (IP) and cutting-edge technologies.
  • Strong background in machine learning research, with a proven track record of publications and contributions to the field.
  • PhD in any AI discipline

Compensation & Benefits

  • Remote working
  • Flexible work hours
  • Equity options
  • Minimum 4 weeks time off per year.