Senior Machine Learning Engineer

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Sona

💵 $121k-$140k
📍Remote - Worldwide

Summary

Join Sona, a rapidly growing AI-native frontline workforce management company, as our new Machine Learning Engineer. You will be part of a small AI/ML team, spearheading the development of Sona's forecasting models. This role involves taking ownership of projects from business idea to deployment, focusing on practical solutions and collaborating with industry experts. You will work with various data tools and technologies, contributing to the success of our clients and the company's growth. The ideal candidate possesses extensive ML experience, strong programming skills, and excellent communication abilities. Sona offers a competitive salary, full remote work flexibility, share options, generous leave, and other comprehensive benefits.

Requirements

  • Extensive industry ML experience, with a track record of deploying ML systems to production, validating and evaluating them
  • Strong programming skills in Python, including the ML/scientific python stack (e.g. numpy, scikit-learn)
  • Strong theoretical understanding of machine learning and how to integrate that machine learning theory with practical decisions
  • Data analysis and technical communication skills. The ability to visualise, communicate and demonstrate your results. (e.g. SQL, pandas, plotting, notebooks)

Responsibilities

  • Spearhead the next step of development of Sona’s best-in-industry forecasting models, creating huge impact for our customers
  • Solve a well defined forecasting problem, and demonstrate Sona as best in class
  • Develop green field areas for machine learning and algorithms across the business
  • Take ownership of the product and outcome end-to-end
  • Take a future machine learning project from business idea to deployed machine learning system
  • Work with our industry experts to really understand what’s happening in our client’s businesses and the realities of working there
  • Work with APIs to generate the datasets, do the data engineering to make them available offline and live, the offline model selection, the live model deployment, monitoring
  • Teach and learn. Explain your approach to people across the business of varying technical expertise, bringing your deep technical knowledge to offer solutions
  • Learn from the wealth of expertise in the business to deepen and broaden your skills

Preferred Qualifications

  • Data engineering: building updating datasets from APIs, database design, strong SQL
  • Cloud platforms, containerisation and deployment. Some Docker experience, CI, Git. Familiarity with Google Cloud Platform (GCP) is a plus
  • Building internal APIs (e.g. Flask)
  • Algorithms, Operation Research “OR” experience (Python PuLP)
  • Online learning / reinforcement learning in a live business setting

Benefits

  • ��95-110k (or local currency equivalent)
  • Full remote and flexible working (with occasional travel for in-person work)
  • Share options
  • 35 days annual leave (25 days standard plus 10 flexible public holiday days)
  • Extra day of leave for every year of service
  • Pension contributions matched up to 5%
  • Comprehensive health insurance
  • Enhanced parental leave & pay
  • Co-working space stipend for those based outside London
  • Bi-annual all expenses paid team retreats
  • The latest Macbook and equipment budget for your home office
  • Professional development budget
  • Unlimited free books

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