Lead Machine Learning Engineer

Empowering enterprises to keep the planet habitable for all!

Reversing the impact of climate change is one of the worlds 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 dont really know how they will get there. And the very first step, of getting emissions measurement right, is hard.

Terrascope is an enterprise-grade, end-to-end decarbonisation SaaS platform. By combining AI-assisted carbon measurement & management with deep industry & sustainability expertise, Terrascope helps solve the data management, emissions reduction planning and implementation challenges that large enterprises face to decarbonise their. operations and complex supply chains.

Publicly launched in June "22, Terrascope is working with customers in multiple industry verticals such as agriculture, food & beverage and consumer packaged goods, as well as horizontals such as manufacturing, technology, transportation and real estate. Terrascope is an innovative player to support enterprises in their green transformation.

Backed by Nupo Ventures (formerly Olam Ventures) and incubated with support from BCG X, Terrascope has now achieved a number of globally recognised accreditations, with more on the way  including being the first CDP Gold Accredited Software provider from Asia and signing The Climate Pledge to be net zero by 2040. Terrascope aims to lead by example and demonstrate that business growth and carbon reduction can go hand in hand.

We are looking for a Lead Machine Learning Engineer to build, deploy and maintain machine learning models at scale, including data pre-processing, feature engineering, model training, post-processing and integration with software applications.

This role will report into the Head of Engineering and will be crucial in shaping the future of climate-tech SaaS products with AI at the core.

In this role you will:
 Be 100% hands-on to build and experiment machine learning models, selecting algorithms and techniques that are most suitable for solving the business problems.
 Train models and tune their hyper-parameters.
 Analyse the errors of the model and design strategies to overcome them. Post-experimentation; optimizing for performance, scalability, and efficiency along with metrics to track progress of the models.
 Explore and visualize data to gain an understanding of it, identifying differences in data distribution that could affect performance when deploying the model in the real world.
 Define validation strategies, pre-processing or feature engineering, data augmentation pipelines to be done on a given dataset.
 Collaborate with our ML Ops team to build a continuous delivery cycle to deploy and operate models in production. Establish dashboards to monitor their performance, inference times, up time, error analysis and precision of models.
 Collaborate with architecture to devise and drive the technical vision, strategy and roadmap for machine learning initiatives.
 Provide technical leadership and guidance to ML engineers/ML ops team.
 Promote a culture of code quality, documentation and knowledge sharing within the team.
 Collaborate with Data Science, Product Management, and other departments to understand business requirements and contribute to the overall success of the projects.
 Collaborate across teams for deploying models into production, and integrating them seamlessly into the existing Terrascope platform.
 Share technical solutions and product ideas through design review, pair programming, code review, and technical discussions.

You should have:
 At least 8+ years leading and building AI/ML models for a SaaS company.
 At least 3 years of experience leading a team of ML Engineers and ML Ops.
 A relevant Bachelors/Master/PhD degree.
 Strong software engineering and coding skills, particularly in machine learning.
 Solid skills in Python and experience in building production grade ML models for various domains/sectors at scale.
 Strong experience in data structures and algorithms
 Strong proficiency in Tensorflow, Keras, PyTorch, scikit-learn and pandas
 Have hands on experience in Big Data and analytics. Any data analysis tools such as Jupyter notebook or google colab
 Be very comfortable with cloud computing (AWS or Azure or GCP)
 A Deep competence in AWS Sage Maker / GCP Vertex / ML Flow
 Demonstrated leadership experience with a track record of successfully leading and developing high-performing teams.
 Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
 Enjoy working in a diverse, dynamic, collaborative, transparent environment where everyone's ideas and opinions are equally valued.

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,