Staff Machine Learning Engineer

$140,000 - $220,000/Yr

Lily Ai - Bodega Bay, CA

Full-time - Senior

Bodega Bay, CA

Publishing Industries

About the position

As a Staff Machine Learning Engineer at Lily AI, you will be responsible for designing and developing scalable platforms and services that drive business impact. This role involves collaborating with machine learning scientists, engineers, and product managers to define the ML roadmap and make key architectural decisions around MLOps, contributing to the overall AI strategy of the company.

Responsibilities

• Define, design, and maintain scalable Machine Learning data pipelines, training infrastructure, and inference systems.
• Optimize, benchmark, and productionize deep learning models to extract high-value product attributes.
• Drive cost efficiency and throughput improvements, owning relevant KPIs.
• Promote and implement software engineering best practices across the team.
• Shape and evolve the technical stack to meet emerging business and technical needs.
• Transition research prototypes into robust, production-ready systems.
• Deploy, monitor, and continuously improve models in production environments.
• Optimize model performance, focusing on memory usage and latency.
• Automate workflows by building efficient pipelines and orchestration frameworks.
• Develop tools and shared libraries to boost team productivity and accelerate development.

Requirements

• 10+ years in building large-scale machine learning solutions and ML Ops practices.
• Experience working with LLM APIs and serving LLMs in-house at scale.
• Proficiency in Kubernetes, RDBMS, and API-driven development.
• Experience with model serving in low-latency, high-throughput use cases.
• Strong emphasis on code hygiene, including review, documentation, testing, and CI/CD practices.
• Proficiency in Python and PyTorch.
• Extensive experience with the scientific Python ecosystem.
• Proficiency in cloud-native application development.

Nice-to-haves

• Experience with Azure.
• Expertise in deep learning-based Computer Vision and NLP models.
• Proficiency 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.
• Master's degree in Computer Science or a related field.

Benefits

• Competitive compensation based on experience and seniority.
• Focus on equity and ownership in compensation policy.