Revolutionizing shopping experience using generative AI and rich messaging technologies to build personalized shopping assistants.

Wizard is at the forefront of transforming the e-commerce landscape by leveraging generative AI and messaging technologies to create personalized shopping assistants. As an ML Engineer at Wizard, you'll be integral to developing sophisticated dialog systems and fine-tuning LLMs. The role combines deep technical expertise in machine learning with practical application in a fast-paced startup environment.

You'll work on cutting-edge problems in NLP, from fine-tuning open-source LLMs to building robust data pipelines and entity resolutions. The position requires strong Python skills and machine learning expertise, though candidates with strong programming backgrounds and a willingness to learn ML are also encouraged to apply.

The role offers significant growth potential in an early-stage startup, with competitive compensation including a $210,000 salary and equity. Wizard provides comprehensive benefits including full medical coverage, dental and vision insurance, mental health support through Spring Health, and generous parental leave policies.

This is an excellent opportunity for experienced ML engineers who want to shape the future of AI-powered shopping experiences. You'll work with modern technologies including PyTorch, GCP, and Kubernetes, while staying at the forefront of the rapidly evolving generative AI landscape. The role combines technical depth with practical impact, making it ideal for those who want to build products that directly enhance consumer shopping experiences.

Senior ML Engineer role at Wizard, focusing on LLM fine-tuning and dialog systems for AI-powered shopping assistance, offering $210k salary with comprehensive benefits.

ML Engineer

Wizard revolutionizes shopping using generative AI and messaging technologies to build personalized shopping assistants that find the best products across the internet.

Wizard is at the forefront of revolutionizing the e-commerce landscape by leveraging generative AI and advanced messaging technologies. We're building a next-generation shopping assistant that personalizes the entire shopping experience for consumers, scanning the internet to find the perfect products based on individual needs.

We're seeking ML Engineers to join our team, with a focus on NLP expertise. The role involves working on sophisticated dialogue systems, from fine-tuning Large Language Models (LLMs) to building robust data pipelines and entity resolution systems. Even if you don't have direct NLP experience but possess strong Python skills and ML exposure, we welcome your application.

As an ML Engineer at Wizard, you'll be instrumental in building and maintaining training pipelines for LLM fine-tuning, working with various architectures and optimizations. You'll be responsible for GPU deployment of models, ensuring optimal performance and resource utilization. The role requires quick problem-solving abilities and the capacity to translate product challenges into ML solutions.

We offer a competitive compensation package starting at $185,000, along with comprehensive benefits including medical, dental, and vision coverage, mental health support through Spring Health, and generous parental leave. Join us in shaping the future of AI-powered shopping experiences while working with cutting-edge technologies in a fast-paced, growth-oriented environment.

The ideal candidate will have 1-3 years of ML experience, with either advanced degrees in relevant fields or exceptional practical experience. You'll work with modern technologies including GCP, Kubernetes, PyTorch, and Node.js, making this an excellent opportunity for growth in the rapidly evolving field of generative AI.

ML Engineer role at Wizard, building AI-powered shopping assistants using LLMs and NLP, offering $185K salary with comprehensive benefits.

Wizard Engineering Jobs

Revolutionizing shopping experience using generative AI and rich messaging technologies to build personalized shopping assistants.