About Lily AI:

Lily AI is a female-founded retail technology company dedicated to empowering retailers and brands by bridging the gap between brand-speak and customer-speak. Combining visual AI with enterprise-grade product attribution capabilities, Lily enhances customer shopping experiences by injecting consumer-centric language throughout the retail technology ecosystem, from site search and demand forecasting to SEO, retail media and beyond.

Specifically, Lily AI allows major retailers and brands to:

• Improve the overall digital shopping experience, nurturing more engaged shoppers with higher eCommerce site conversion
• Achieve 8-9 digit revenue lifts
• Assign 10x more attributes for each product - from fit to style, from embellishments to occasion, seasonal and even micro-trends
• Better understand customer shopping dynamics to inform future product development and assortments as well as improve forecasting

Overview:

At Lily AI, we’re serious when we say that we are committed to creating an amazing culture where each and every team member can thrive. First and foremost, we’re not just colleagues; we’re like a family - known for being caring, encouraging and always going the extra mile to help each other out. It’s startup world and as those who have worked for a startup know, every day is vastly different than the day before and as such, we place premium value on high empathy - both with our team members and our clients, fostering an environment where we listen and support each other through challenges and triumphs alike.

And speaking of the startup world, every single employee, without exception, is offered stock options because we believe everyone should be rewarded for their hard work and drive for results.

And speaking of results, earlier this Spring, we were honored to be included in the prestigious Top 100 Retail Tech Companies list released by CB Insights. While that was a proud moment, our proudest achievement is the top ratings we consistently receive from our own employees as reflected on Comparably.

Join us on our journey to transforming the world of digital commerce!

We are looking for a skilled Machine Learning Engineer to join our team and help design, develop, and deploy advanced machine learning models and solutions for a variety of business problems. The successful candidate will collaborate with data scientists, software developers, and product managers to transform experimental models into production-ready systems, ensuring scalability, efficiency, and robustness.

In this role, you will:

As part of the Machine Learning team, you will have the opportunity to reimagine and build the next-generation personalization that enables brands and retailers to understand the cognitive attributes of customers online and the 'why' behind 'what they do' in their journey by pushing the boundaries of our ML systems and algorithms.

• Own the data, training and serving pipelines of Lily’s ML solutions from an engineering standpoint.

• Productionize ML based solutions as developed by our ML Scientists.

• Optimize and fine-tune machine learning models and algorithms using appropriate programming languages, libraries, and frameworks.

• Design and build ML serving pipelines with stringent SLAs.

• Continuously monitor and evaluate the performance of machine learning models in production, identifying areas for improvement and optimization.

• Adhere to software engineering best practices while maintaining our tech stack.

• Troubleshoot and resolve issues related to system integration, model performance, and data quality.

• Facilitate customer POCs and attend to escalations

What we consider critical for this role:

• Proficiency in Python, Pytorch and SciPy.

• Expertise in real-time serving and optimization tools for deep learning, e.g. Triton, TensorRT, PyTorch JIT, TorchScript, ONNX.

• Expertise in developing solutions on cloud platforms like AWS and Azure.

• Expertise in developing and maintaining efficient, scalable, and robust machine learning systems, integrating models into existing software systems and applications.

• Expertise in distributed systems concepts.

• Familiarity with Large Language/Multi-Modal Models.

• Strong understanding of machine learning concepts, techniques, and algorithms, with experience in applying these methods to real-world problems.

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.

Compensation:

Compensation is competitive and will be determined based on a combination of experience, seniority, internal, external equity and location. For some context: this position in the US would pay between $135,000-$180,000 USD per year, depending on experience and seniority. In other regions, compensation will be adjusted for local currency and local market rates. Lily AI compensation policy is calculated with a focus on equity and where employees can thrive.