RRemoteville
Privasee logoPrivasee

Machine Learning Engineer

Skills
A/B TestingAlgorithmsArtificial IntelligenceData ScienceExploratory Data AnalysisMachine LearningPattern Recognition
Role

What the job involves

The main requirements, responsibilities and hiring steps.

Requirements

  • 4+ years of professional experience in the field of ML/AI
  • Highly proficient in Python, ML python packages like pytorch, huggingface and scitkit-learn, NLP, Kubernetes
  • Solid understanding of classical ML algorithms
  • Superior ability to cleanse/prepare datasets for training and performance tracking
  • Good understanding of statistical concepts, particularly in the context of A/B testing
  • Familiarity with fundamental concepts of deep learning and transformer-based architectures
  • A passion for LLMs and the growing ecosystem around them (e.g. Langchain), and hands-on experience with using them in production
  • Strong programming and algorithmic skills
  • Experience working with big data technologies
  • Self-directed, able to contribute and see ahead of the current development timeline
  • English working proficiency and communications skills (verbal and written)

Nice to have

  • Experience in systems design with the ability to architect and explain machine learning pipelines
  • Data visualisation skills
  • Startup experience as an early employee or founder

Day to day

  • You will help us expand our AI products, working collaboratively and interactively, using technology to deliver solutions to complex problems.
  • You will closely work together with our CTO and will have significant decision-making power on the technologies and architecture that we use to build out the platform.
  • You will be at the forefront of revolutionising the legal-tech industry.
  • You’ll be the founding member of our ML/AI team, and focus on bringing this next generation of AI-powered features to Privasee.
  • You will combine your AI expertise and product expertise improve on our existing legal recommendation system and create new products.
  • You'll use state of the art LLMs and prompting techniques to create features, train models in-house where appropriate, and stay up to date with changes in the field.
  • Working closely with operations teams to validate that your ideas will bring value, implementing them in collaboration with front and backend engineers, and creating systems to monitor their ongoing performance.
  • To conduct exploratory data analysis on customer data and industry trends.
  • Develop ML/Deep learning algorithms.
  • Analyse the performance of models and facilitate continuous improvement.
  • End-to-end ownership of ML problems.
  • Significant decision making power on the technologies and architecture that we use to build the platform.

Hiring process

  • Phone Screening (10’)
  • Practical Task
  • Call with both co-founders (30’)
  • Short Online Assessments (reasoning, cognitive, personality)
  • Technical Interview (30’)
  • Decision