Machine Learning Engineer Generative AI

Join our cutting-edge food-tech company that pioneers plant-based food creations using

data-driven methods. We're looking for an experienced and passionate Machine Learning

Engineer to drive our R&D initiatives. This role primarily focuses on the research, prototyping,

and development of state-of-the-art data-driven algorithms and theoretical solutions, especially

in the domains of geometric machine learning and generative methods for recipe generation.

Key Responsibilities:

- Research & Development: Lead R&D initiatives by exploring, prototyping, and developing

state-of-the-art generative AI models for recipe generation.

- End-to-End ML Pipeline: From data acquisition and preprocessing to model training and

validation, be the mastermind behind our innovative prototypes.

- Data Analysis & Visualization: Dive into complex datasets to uncover opportunities and

insights, shaping the direction of our research efforts.

- Data Processing: Design pipelines for handling large-scale and unstructured data, ensuring it's

ready for high-quality modeling.

- Collaboration: Work hand-in-hand with data scientists to refine and enhance machine learning

models, pushing the boundaries of what's possible.

- Robust Prototyping: Ensure that all prototypes are scalable, efficient, and ready for further

refinement or production consideration.

Minimum Qualifications:

- A bachelor degree in math, engineering, computer science, or a related field.

- Mathematical maturity.

- 4+ years of hands-on experience in Machine Learning R&D or a similar research-focused role.

- Solid foundation in data structures, data modeling, and software architecture.

- Profound understanding of deep learning theories, architectures, and libraries such as

TensorFlow, PyTorch, and Keras.

- Experience or interest in graph neural networks or similar techniques is a major plus.