Staff Machine Learning Engineer
About The Position
Deploy is an AI intelligence infrastructure company providing access to open-source and proprietary AI models. It operates an optimized inference engine for leading open-source large language models and offers proprietary models for content safety, AI and deepfake detection, sponsorship intelligence, and intellectual property and publicity protection. The company has more than 250 employees across San Francisco, Seattle, New York, and Delhi. The Staff Machine Learning Engineer will help develop and productionize machine learning models, from prototyping neural networks through launching and improving them in production. The role involves working with large-scale datasets, learning technologies across the machine learning stack, taking ownership of projects, building machine-learning-powered products from the ground up, and planning scalable, maintainable data pipelines. The position also contributes to product and backend systems, engineering practices, cross-functional work, mentorship, and strategic planning.
Requirements
- Bachelor's degree in computer science or a related field.
- 8 or more years of experience building web applications.
- Experience successfully implementing highly available distributed systems or microservices.
- Experience delivering scalable backend APIs.
- Strong interpersonal and communication skills, with a bias toward action.
- Experience writing code and training across distributed systems.
- Ability to understand and make well-reasoned tradeoffs when designing features.
- 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 lead end-to-end development of new products.
Responsibilities
- Design and code neural networks; gather and refine data; train and tune models; deploy models at scale with high throughput and uptime; and analyze production results to continuously improve accuracy and speed.
- Write and maintain scalable, performant code that can be shared across platforms.
- Suggest and implement improvements to the product and core backend systems.
- Improve engineering standards, tooling, and processes.
- Develop novel, accurate, and performant machine learning algorithms for use at scale.
- Conduct metric-driven research experiments to improve model performance.
- Mentor and help onboard machine learning engineers.
- Lead cross-functional collaboration with other teams.
- Contribute to defining strategic direction and planning the roadmap.
- Maintain awareness of industry best practices for data maintenance and handling as relevant to the role.
- Follow policies, guidelines, and procedures for protecting information assets.
- Report actual or suspected security or policy violations or breaches to an appropriate authority.
- Lead end-to-end development of new products.
Benefits
- Stock options may be offered in addition to base salary.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
