Staff 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 technologies such as computer vision, natural language processing, machine learning, and vertical-specific large language models (LLMs), the Lily platform enhances customer shopping experiences by analyzing product catalogs and enriching assortments with natural language. The optimized data is distributed across a retailer's ecosystem—from their website to Google Ads—delivering considerable revenue lift through improved product attribution, enhanced discovery, increased traffic, and higher conversion rates. Learn more at www.lily.ai.

Overview: As a Staff Machine Learning Engineer, you will design and develop scalable platforms and services focused on business impact while raising the bar for technical excellence. You will collaborate with machine learning scientists, engineers, and product managers to define the ML roadmap, make architectural decisions around MLOps, and contribute to the overall AI strategy of the company.

Your day-to-day will include:

• Defining, designing, and maintaining scalable Machine Learning data pipelines, training infrastructure, and inference systems.
• Optimizing, benchmarking, and productionizing deep learning models to extract high-value product attributes for revenue enhancement in onsite search and Google Ads offerings.
• Driving cost efficiency and throughput improvements while owning relevant KPIs.
• Promoting and implementing software engineering best practices across the team.
• Shaping and evolving the technical stack to meet emerging business and technical needs.
• Transitioning research prototypes into robust, production-ready systems.
• Deploying, monitoring, and improving models in production environments, focusing on performance optimization regarding memory usage and latency.
• Automating workflows by building efficient pipelines and orchestration frameworks.
• Developing tools and shared libraries to boost team productivity and accelerate development.

What we consider critical for this role:

• Experience: 10+ years in building large-scale machine learning solutions and MLOps practices, including working with LLM APIs and serving LLMs in-house at scale.
• Technical Expertise: Kubernetes, RDBMS, API-driven development, model serving in low-latency, high-throughput use cases; observability, data pipeline design, service scaling, and cost optimization.
• Code Quality: Strong emphasis on code hygiene, including review, documentation, testing, and CI/CD practices.
• Programming Skills: Proficiency in Python and PyTorch, with extensive experience in the scientific Python ecosystem.
• Cloud Development: Proficiency in cloud-native application development.
• Mindset: Action-oriented with the ability to articulate complex concepts into thoughtful, actionable iterations.

What will set you apart from other candidates:

• Proficiency in writing high-performance production code in Python, particularly using frameworks like PyTorch.
• Excellent communication and interpersonal skills.
• Experience with Azure.
• Expertise in deep learning-based Computer Vision and NLP models.
• Familiarity with tools for managing the ML lifecycle, such as MLFlow and Kubeflow.
• Proficiency with real-time serving and optimization tools for deep learning, including TFX, PyTorch JIT, TorchScript, and Seldon.
• A Master's degree in Computer Science or a related field.

Details: We are currently hiring from the following US states, Canada, and Latin America (candidates must be residing in these locations or open to relocating):

• Alabama
• Arizona
• California
• Colorado
• Connecticut
• Florida
• Georgia
• Illinois
• Indiana
• Massachusetts
• Minnesota
• Nevada
• New Jersey
• New York
• North Carolina
• Oregon
• Pennsylvania
• Rhode Island
• Tennessee
• Texas
• Utah
• Virginia
• Washington

Compensation is competitive and will be determined based on experience, seniority, internal and external equity, and location. For context, this position in the US would pay between $140,000 - $220,000 USD per year, depending on experience and seniority. In other regions, compensation will be adjusted for local currency and market rates. Lily AI's compensation policy focuses on equity and ownership.