Senior Applied Scientist, Machine Learning
About Lily AI:
Lily AI is a female-founded retail AI company empowering retailers and brands by bridging the gap between merchant-speak and customer-speak. Leveraging computer vision, natural language processing, machine learning, and vertical-specific large language models (LLMs), Lily AI enhances customer shopping experiences by injecting consumer-centric language throughout the retail technology ecosystem. Interoperable with leading eCommerce platforms, Lily AI maximizes existing tech investments to deliver upwards of 9-figure revenue lift through improved product attribution, enhanced discovery, and higher customer conversion. Learn more at www.lily.ai.
We are seeking a talented and highly motivated Machine Learning Scientist to join our team and contribute to the development and deployment of cutting-edge machine learning models and algorithms. The successful candidate will work closely with cross-functional teams to solve complex business problems, improve existing systems, and push the boundaries of what is possible with machine learning.
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.
- Using proven techniques in computer vision and NLP to solve business challenges in the domain of deep product attribution, item setup and demand forecasting.
- Conduct research on the latest machine learning techniques, tools, and frameworks to identify and recommend potential improvements to existing models and systems.
- Design and perform experiments to validate and refine model performance, using both quantitative and qualitative methods.
- Assist in the development of production-ready code and integrate machine learning models into existing systems and workflows.
- Define the training-data roadmap for various ML tasks.
- Continuously monitor and analyze model performance in production, identifying opportunities for improvement and optimization.
- Maintain up-to-date knowledge of industry best practices, trends, and advancements in the field of machine learning.
- Collaborate with internal stakeholders for various org initiatives.
- Facilitate customer POCs and attend to escalations.
What we consider critical for this role:
- 8-12+ years of experience in building large scale machine learning solutions.
- Expertise in Python and PyTorch.
- Experience with Large Language/Multi-Modal Models.
- Experience with ML frameworks & platforms like Weights & Biases, PyTorch Lightning and HuggingFace.
- Experience in data wrangling and preprocessing techniques.
- Strong problem-solving, critical thinking, and analytical skills.
- Familiarity with cloud platforms like Azure.
- Familiarity with distributed systems.
- Master's or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related field.
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 $160,000-$175,000 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.