Description:

Wizard is seeking a Senior Machine Learning Engineer to work remotely in the USA, focusing on dialog systems and generative AI.
The role involves building and maintaining a training pipeline for fine-tuning open-source LLMs, testing various architectures and configurations.
Responsibilities include serving and deploying LLMs on GPUs, formulating product issues into ML problems, and triaging customer issues related to model/system shortcomings.
The candidate will need to stay updated with developments in the generative AI space and incorporate them into the system.

Requirements:

A Master's or Ph.D. in computer science, mathematics, or a related quantitative discipline, or exceptional work experience in ML engineering is required.
Candidates must have at least 3 years of experience in machine learning.
Experience in developing machine learning-driven products at scale is essential.
Proficiency in solving problems using Machine Learning with PyTorch is required.
A strong understanding of designing ML systems in production at scale and identifying performance bottlenecks is necessary.
Practical experience with large data systems, data models, and both batch and streaming data pipelines is expected.
Candidates should be able to quickly learn the tech stack, which includes GCP, Kubernetes, Airflow, Pandas, PyTorch, Python, and Node.js.
Extensive experience with model deployment using frameworks like Flask or FastAPI is required.

The position offers the opportunity to be part of an early-stage startup with significant growth potential.
Competitive compensation packages are provided, including equity.
Comprehensive health benefits include high-quality medical coverage, dental and vision insurance, OneMedical memberships, mental healthcare through Spring health, eyewear benefits, and a Rightway Health Guide.
A 401(k) plan and life & disability insurance are covered by Wizard.
Work/life balance is supported with flexible PTO, sick time, 12 paid holidays, and 16 weeks of parental leave for primary and secondary caregivers.