Machine Learning Engineer (Generative AI)
Role details
Job location
Tech stack
Job description
We are looking for a Machine Learning Engineer or scientist who will be converting abstract, high-level goals into concrete, measurable requirements. They will be proposing, implementing, evaluating, and shipping different AI/ML technologies to improve data quality or deliver user facing features. This role will be collaborating with various partners, including engineering orgs and designers to architect the best overall system.
Requirements
In this role, you'll work alongside world-class engineers and scientists to develop innovative AI/ML solutions that enhance user experiences. The ideal candidate takes initiative, demonstrates ownership from concept to production, is not afraid to dive deep into data, and is hands-on in building robust, real-world solutions. They thrive in a fast-paced environment and bring resilience and curiosity to continually improve in pursuit of excellence.
5+ years of experience in building large-scale machine learning systems\n2+ years of experience in one or more of the following ML areas: generative AI models (e.g. Transformers, LLMs, VLMs, MLLMs), computer vision or knowledge graph\nExperience working with large-scale and real-world datasets\nMetrics-driven and passionate about delivering models that produce high-quality, user-facing results\nStrong programming skills and hands-on experience with machine learning tools and libraries such as PyTorch, TensorFlow, Scikit-learn\nStrong knowledge of Spark or other related big data technologies\nFamiliarity with cloud platforms such as AWS, Google Cloud Platform, or Azure
\nMasters or PhD degree in Machine Learning, Computer Science, Electrical/Computer Engineering, or related fields.\nExperience shipping a complex AI system, including research and leveraging generative AI models\nExcellent written and oral communication skills\n\n