Pendulum Systems is looking for a highly motivated and detail oriented Machine Learning Engineer to join our team.
As an ML Engineer at Pendulum, you will have the opportunity to push the boundaries of the field in AI+supply chains, by building, designing and deploying cutting-edge machine learning solutions. You will work on problems that bring a direct impact to saving lives and enabling governments to do more with less. The problems we address need careful transformation of state-of-the-art machine learning techniques to enable robust performance when deployed in the real world.
What we will do together:
- Gather and preprocess large datasets to be used for training machine learning models. This work may involve cleaning data, handling missing values, and transforming data into suitable formats for analysis.
- Identify and create relevant features from the raw data to improve the performance of machine learning algorithms.
- Design and develop machine learning models/architectures and algorithms based on project requirements. This work includes for instance selecting appropriate algorithms, tuning hyperparameters, and optimizing for performance and efficiency.
- Work closely with the engineering team to deploy machine learning models into production, ensuring they are scalable, reliable, and maintainable.
- Collaborate with a highly diverse and completely remote team.
- Document and publish your work at high-impact machine learning conferences.
What you will need:
- Masters or Doctorate degree in computer science, electrical engineering, computer engineering, mathematics, or another related field.
- Solid programming experience in Python. Proficiency in popular machine learning libraries/frameworks like, PyTorch, scikit-learn, etc.
- Strong understanding of machine learning algorithms, data structures, and statistics. Experience with deep learning algorithms and frameworks is a plus.
- Knowledge of software engineering principles, version control systems (e.g., Git), and best practices in software development.
- Problem-solving skills and the ability to think critically about complex technical challenges.
- Solid communication skills and collaboration experience
- Curiosity about new things.
Definite plus points:
- Publication or contributions to top-tier ML venues
- Proficiency in mathematical optimization
- Experience with LLMs