Senior Machine Learning Engineer

Salary: CHF 110’000 - 140’000 per year

Requirements:

• Masters or PhD Degree in Data Science/Computer Science with a focus on ML or equivalent practical experience
• Typically 5+ years of experience with Machine Learning algorithms in either an academic or industry setting
• Structured and self-reliant approach

Responsibilities:

• Software Development:
• Design and develop clean and maintainable software solutions using Python, leveraging industry best practices and design patterns, ensuring high code quality
• Conduct code reviews and provide constructive feedback to ensure the overall quality and consistency of the codebase
• Machine Learning
• Bridge the gap between the business case and the technical solution to solve it, while focusing on choosing the right tool for the job
• Develop and maintain custom transformer-based NLP architectures
• Understand and reason about state-of-the-art research, extract relevant ideas from it and use it to improve our models
• Work on all aspects of the end-to-end prediction service, including data-management, model improvements, monitoring and scalability

Technologies:

• Cloud
• Docker
• Kubernetes
• Machine Learning
• Python
• RabbitMQ
• Redis
• TensorFlow
• GCP

More:

At BLP, we develop a cutting-edge product for automated document processing. Machine learning is at the core of our business, and we continuously strive to enhance the quality of our predictions using state-of-the-art machine learning models. Working in a startup presents exciting challenges, such as scaling both our team size and the processing volume to accommodate growing demands. Throughout this journey, we prioritize a simple and maintainable architecture to ensure efficient operations. To stay at the forefront of technology, we leverage a modern tech stack that includes Python, Docker, TensorFlow, Redis, RabbitMQ, and Micro Services on a Kubernetes Cluster, deployed as Software-as-a-Service on one of the big cloud providers. In our team, we value the opportunity for our engineers to shape the future and have a significant impact on various aspects. This influence spans areas such as organizational structure, the coding process, team culture and organization.

last updated 40 week of 2025