Senior Machine Learning Engineer
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 looking for a Senior Machine Learning Engineer to join our team and help 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:
- 4-6+ years of ML experience with proficiency in Python, Pytorch and SciPy.
- Expertise in ML Ops and Kubernetes.
- 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.
Currently, we are hiring from the following states – (candidates must be in current residence or open to relocating):
Alabama • Arizona • California • Florida • Georgia • Illinois • Indiana • Massachusetts • Minnesota • Nevada • New Jersey • New York • North Carolina • Rhode Island • Tennessee • Texas • Utah • Virginia • Washington
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 $175,000-$190,000 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.