Machine Learning Engineer (Multiple Positions)

Machine Learning Engineer (Multiple Positions)

Full Job Description:
Gemini AI is revolutionizing how sport organizations interact with data. Our self-learning platform enables
sport coaches and team executives to leverage the power of artificial intelligence in unprecedented ways. As part of our expansion strategy, we are now seeking to fill multiple data engineering (ML) roles. The successful candidate will work in a variety of machine learning projects alongside a multidisciplinary team of experts in various sport related fields including data science, sport science, software development, project management and strategy. Your primary scope of work is to build on request state-of-the-art machine learning models to support our client’s decision making process.

Location: Remote

Position: Possibility for both full-time or part-time roles.

About You: Self-driven, solutions approach. Willing and excited to be a part of a start-up environment where evolutions are rapid. Obsessed with helping our teams win.

Responsibilities:

  • Select, research and transform datasets to answer research questions.
  • Research and implement Machine Learning tools based on requirements.
  • Ongoing monitoring, training and retraining of models in production.
  • Ability to design and execute solution pathways, accounting for near-term product deliverables.
  • Support our software development team to continue developing our platform.
  • Interpret model performance and facilitate the explanations of results according to context as well as tailoring to non-technical audiences.

Skillset:

  • Experience implementing machine learning models to solve complex problems. Previous experience in sports is preferred but not mandatory.
  • Experience with various programming languages, preferably Python and Javascript.
  • Experience working with open-source machine learning frameworks such as Keras, PyTorch, TensorFlow, SciPy, Scikit-learn, etc.
  • Research design and implementation. Ability to work independently through each step of the data pipeline. Take ML models from research to production.
  • In depth cloud-computing experience (AWS, Microsoft, Snowflake, etc).
  • Experience working with relational databases and query authoring (SQL)
  • Able to communicate clearly and concisely.

Requirements:

  • BS in Computer Science, Mathematics or similar field; Master’s degree is a plus.
  • Embrace the start-up lifestyle. Self-motivated, obsessed with learning and growth, enjoys working within a fast-evolving ecosystem.

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