December 6
• About Pathway: Pathway is an enabler for Live AI, allowing organizations to run contextualized ML models connected to ever-changing enterprise data. • The Opportunity: We are currently searching for 2 ML/AI Engineers with a solid software engineering backbone to prototype and deliver end-to-end Machine Learning projects with enterprise data. • You Will: help design experimental end-to-end ML/AI pipelines, improve/adapt AI pipelines for production, contribute high-quality production code, design benchmark tasks and perform experiments. • The results of your work will play a crucial role in the success of both our developer offering and client delivery.
• Cover letter • A graduate of a 4+-year university degree in Computer Science, where you have received A-grades in both foundational courses (Algorithms, Computational Complexity, Graph Theory,...) and Machine Learning courses. • Passionate about delivering high-quality code and solutions that work. • Good with data & engineering innovation in practice - you know how to put things together so that they don't blow up. • Experienced at hands-on Machine Learning / Data Science work in the Python stack (notebooks, etc.). • Experienced with model monitoring, git, build systems, and CI/CD. • Respectful of others • Curious of new technology - an avid reader of HN, arXiv feeds, AI digests, ... • Fluent in English
• Type of contract: Full-time, permanent • Preferable joining date: January 2025. The positions are open until filled – please apply immediately. • Compensation: competitive base salary (80th to 99th percentile) based on profile and location + Employee Stock Option Plan + possible bonuses if working on client projects. • Location: Remote work. Possibility to work or meet with other team members in one of our offices: Paris, France, or Wroclaw, Poland. Possibility to visit our Menlo Park, CA headquarters for several months.
Apply NowNovember 8
51 - 200
Tooploox seeks a Machine Learning Engineer for software applications using ML algorithms.
September 13
Manage ML infrastructure and deploy models as part of a software engineering team.