Machine Learning Engineer

**Join us on a mission to save the planet**

Reversing the impact of climate change is one of the world’s biggest challenges. And businesses have a responsibility to lead the way. While individual consumer choices are important, over 80% of all the emissions reductions necessary for the world to reach Net-Zero, require business-level action. But despite the growing momentum and ambition from companies around the world to set Net-Zero goals, there are significant challenges to delivering on these ambitions. Business leaders don’t really know how they will get there. And the very first step, of getting emissions measurement right, is hard.

Terrascope is a smart carbon management and accounting platform that empowers corporations to decarbonise their operations, portfolios and supply chains in a trusted, confident, and secure manner. We are on a journey to build digital tools and analytics, datasets and algorithms, and an ecosystem of technical expertise and partnerships needed for companies to optimise their climate strategy

Terrascope is backed by one of the world’s largest food and agri companies and global leader in climate action and sustainability. With their significant strategic advantage and secure funding, the venture is uniquely positioned to drive profit with purpose; driving decarbonisation in supply chains while generating outsized financial returns.

We are looking for a highly capable **machine learning engineer **to optimize our machine learning systems and productionize them at scale. You will be evaluating existing machine learning (ML) processes, performing statistical analysis to resolve data set problems, and enhancing the accuracy of our AI software's predictive automation capabilities.

To ensure success as a machine learning engineer, you should demonstrate solid data science knowledge and experience in a related ML role deploying model systems. A first-class machine learning engineer will be someone whose expertise translates into the enhanced performance of predictive automation software.

**In this role you will**:

- Collaborate with engineering teams to make sure ML infrastructure is fit for purpose
- Consult with managers to determine and refine machine learning objectives.
- Design machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
- Ensure that algorithms generate accurate user recommendations.
- Solve complex problems with multi-layered data sets, as well as optimize existing machine learning libraries and frameworks.
- Develop ML algorithms to optimally analyze huge volumes of data to make predictions.
- Run tests, performing statistical analysis, and interpreting test results.
- Document machine learning processes.
- Keep abreast of developments in machine learning.
- Develop systems for data scientists to deploy models

**You should have**:

- Advanced degree in computer science, math, statistics or a related degree.
- Advanced degree in machine learning, neural networks, deep learning or related fields.
- Strong analytical, problem-solving and teamwork skills.
- Software engineering skills.
- Experience in data science.
- Coding and programming languages, including Python, Java, C++, C, R and JavaScript.
- Experience in working with ML frameworks.
- Experience working with ML libraries and packages.
- Understand data structures, data modeling and software architecture.
- Knowledge in computer architecture.

**Even better if you are**:

- Certification in ML systems for Azure or AWS or GCP
- We're committed to creating an inclusive environment for our strong and diverse team. We value diversity and foster a community where everyone can be his or her authentic self._