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Staff Machine Learning Engineer
2 months ago
Culture Amp is a leading employee experience platform that empowers companies to transform employee engagement, drive performance management, and develop high-performing teams. With a comprehensive employee dataset and people science, Culture Amp helps innovative companies like Canva, On, Asana, Dolby, McDonalds, and Nasdaq create a better world of work.
Role OverviewWe are seeking a Staff Machine Learning Engineer to accelerate our capability in building and enhancing machine learning platforms powered by AI and Large Language Models (LLMs). As part of the Machine Learning Platform (MLP) team, you will work with data scientists and engineers to provide a central LLM gateway that enables product teams to leverage the power of Gen AI.
Key Responsibilities- Participate in code reviews, architecture discussions, and contribute to best practices in ML engineering
- Collaborate and guide other engineers in your team through pair/mob programming, writing solution designs, or giving feedback on pull requests
- Stay up-to-date with the latest advancements in machine learning and AI technologies and integrate them into our products
- Play a huge role in coaching and uplifting other engineers in the team
- Play a tech lead role for the team and work with leadership to define long-term technical vision
- Passionate about machine learning, AI, and LLMs
- Advocate of sensible, ethical, and responsible use of AI
- Able to influence others without authority, working collaboratively with diverse engineers and cross-functional teams
- A proactive and clear communicator
- Self-motivated and able to work independently
- Employee Share Options Program
- Programs, coaching, and budgets to help you thrive personally and professionally
- Access to external providers for mental wellbeing and coaching support
- Monthly Camper Life Allowance
- Team budgets dedicated to team building activities and connection
- Intentional quarterly wellbeing pauses
- Extended year-end breaks
- Excellent parental leave and in-work support program
- 5 Social Impact Days a year
- MacBooks and a work-from-home office budget
- Medical insurance coverage