Sherpany is the Swiss market leader for meeting management software. Since its founding in 2011, it has pursued the goal of creating a world in which every meeting counts. Over 400 European companies and 12,000 decision-makers are already using Sherpany with the aim of making their business relevant meetings more productive and thereby increasing corporate success. With headquarters in Zurich and 130 Sherpanees from 27 different nationalities, we are an international company with a flat hierarchy, in which you can take lot of responsibility and your ideas are always welcome.
Your mission as Machine Learning Engineer is to:
- Develop, deploy, and optimize self-hosted ML pipelines, focusing on LLM and NLP model performance and reliability;
- Collaborate closely with backend, security and DevOps teams to align LLM model architecture with infrastructure and security protocols;
- Design workflows for prompt templating, orchestration and optimization of LLMs to power Sherpany’s product features;
- Manage model performance monitoring, logging and fine-tuning for continuous improvements;
- Develop backend solutions that securely interface with ML models, ensuring efficient API performance and scaling;
- Play a pivotal role in translating data science insights into actionable products;
- Stay current with AI/ML industry developments and apply best practices to Sherpany’s platform.
What we will love about you:
- Strong background in ML and NLP with proven experience, preferred in self-hosted LLMs (e.g. LLaMA);
- Proficiency in backend engineering, especially in Python and building scalable API integrations;
- Skilled in Docker and Kubernetes/similar for model deployment within on-prem infrastructure;
- Experience with data pipelines, logging and monitoring for large-scale ML models;
- Solution-oriented team player with a proactive, autonomous work style and strong communication verbal and written skills in English.
How you can imagine us:
- You will be part of an international company with a flat hierarchy where you can take on a lot of personal responsibility and your ideas are always welcome;
- To ensure your work-life balance, we offer flexible working hours, remote-first policy and the possibility of unpaid vacation after your first year with us DIGITAL NOMAD @SHERPANY;
- Your personal and professional development is important to us, which is why we offer financial support for further education, training, etc.
- Your personal well-being is important to us - our partner nilo.health supports you in this;
- We work with new technologies and Apple MacBooks, which will be provided to you when you start;
- Last but not least: Our corporate culture means a lot to us, which is why we regularly organize great team events and cultivate a value-oriented cooperation.
Recruiting process:
- Interview with our Talent Acquisition Specialist
- Show us your skills in a Challenge
- Technical interview with our experts & Get to know our Squad Lead and the Product Manager
- Meet the Team members & our VP Engineering
- Job offer
Signing Bonus: If you apply before 31st December 2024, you'll get a cool CHF 1,000 in your first paycheque! Speak to your Talent Acquisition Specialist for more details
Milestones
1-3 months
- Understand Sherpany as a product and technology, the Product Team organization, and how we work within the lab squad and backend/data science chapters;
- Gain familiarity with Sherpany’s on-prem infrastructure, technology stack, and self-hosted LLM systems;
- Schedule coffee chats with every squad member, your Sherpybuddy and start building connections with the backend members.
3-6 months
- Get feedback on how you are doing as an ML engineer within the squad/chapter;
- Actively contribute to the squad’s AI-feature projects and initiatives (ML model deployment and backend integration);
- Gain solid knowledge of our technology stack, tooling used in Sherpany, AI architecture and infrastructure;
- Have your first interactions with all colleagues across Sherpany you will work with on a regular basis, including TechLeads, Jedis (our backend chapter), our Security team and DevOps team.
6+ months
- Take ownership of LLM optimization initiatives and propose improvements for efficiency and scalability;
- Contribute to the roadmap for on-prem LLM implementations and model tuning.
Are you ready for the challenge? We look forward to receiving your application!
