EXPERIENCE:

As a Machine Learning, Software Engineer you will have autonomy to shape the design of the machine learning models, and software development road-map. You will collaborate with cross-functional teams, contribute to product innovation, and mentor team members, driving our mission to mitigate risks in agriculture.

EXPERIENCE REQUIRED:

• Master’s or Ph.D. in Data Science, Machine Learning, Statistics, Computer Science, or a related field.
• Hands on experience in Machine Learning or data engineering and Python.
• Expertise in C#, C++, Go or Java will be considered.
• Experience with Cloud technologies and platforms (Azure, AWS, GCP).
• Knowledge of remote sensing data, time-series analysis, and geospatial systems is beneficial.
  You will have the chance to directly impact the growth of this start-up and shape the future of climate technology initiatives. You will have the autonomy to shape the companies software and product offering. This is a Sydney based, hybrid role.
  Please apply for immediate consideration

ABOUT THE ROLE:

This position offers the opportunity to join a growing Climate-Tech business innovating the space by leveraging advanced analytics, machine learning, and domain expertise.
They are seeking a Machine Learning, Software Engineer with experience productionizing models developed by Data Scientists. You will Lead the development and deployment of machine learning algorithms, geospatial analysis, and other advanced analytical methods, helping to evolve their core software and product offering.

KEY RESPONSIBILITIES:

• Help shape the software engineering roadmap, staying informed on market trends in climate modelling and agricultural technologies.
• Productionize models into the companies cloud SAAS offering.
• Lead the development of machine learning algorithms, geospatial analyses, and advanced analytical methods.
• Ensure the quality, integrity, and security of data used in all initiatives.
• Work closely with product and engineering teams to deliver scalable solutions.
• Work closely with the data science team and Head Of Product.
• Provide technical oversight and drive best practices within the team.