Staff Machine Learning Engineer

Location: San Francisco, United States; on-site

Base salary: $200,000–$300,000 per year, with potential stock options.

Company

Deploy is an AI intelligence infrastructure platform providing optimized inference for open-source and proprietary AI models, including models for content safety, deepfake detection, sponsorship intelligence, and intellectual property and publicity protection.

What you will do

• Design, implement, train, tune, deploy, and continuously improve machine learning models for production use cases.
• Gather and refine data, analyze real-world results, and improve model accuracy, speed, throughput, and uptime.
• Write and maintain scalable, performant, cross-platform code and contribute improvements to product and core backend systems.
• Develop novel ML algorithms and conduct metric-driven research experiments at scale.
• Improve engineering standards, tooling, processes, and scalable data pipelines.
• Mentor and onboard ML engineers, lead cross-functional collaboration, and contribute to strategic direction and roadmap planning.

Requirements

• Bachelor’s degree in computer science or a related field.
• 8+ years of experience building web applications.
• Experience implementing highly available distributed systems and microservices.
• Experience delivering scalable backend APIs and writing code and training across distributed systems.
• Expertise in machine learning frameworks such as PyTorch or TensorFlow.
• Expertise in scripting languages such as Python and/or shell scripts, particularly for data analysis.
• Subject matter expertise in at least one machine learning focus area, such as computer vision or natural language processing.
• Ability to understand and make well-reasoned tradeoffs when designing features, strong interpersonal and communication skills, and a bias toward action.
• Ability to lead the end-to-end development of new products.

Culture & Benefits

• Opportunity to work at a fast-growing AI startup with a direct impact on company development.
• Exposure to new technologies across the machine learning stack and terabyte-scale datasets.
• Base compensation includes a potential stock option component.
• Information security policies and procedures must be followed, with suspected violations reported to the appropriate authority.

Hiring process

• Artificial intelligence tools may support application, resume, and response review and identify potential inconsistencies or verification signals.
• Final hiring decisions are made by humans.