Senior Machine Learning Engineer

Hive; San Francisco (CA); On-site; USD 160,000 - 250,000; Full time

Job summary

Deploy is seeking a Senior Machine Learning Engineer to push ML models from prototype to production at scale in San Francisco. You will design, train, and deploy models on terabyte-scale datasets, building robust data pipelines and scalable backend integrations.

The role emphasizes ownership, high code quality, automated testing, and collaboration with cross-functional teams to advance our AI platform.

Qualifications

• Bachelor's degree in CS or related field required.
• Minimum 5 years building production-scale ML models.
• Solid experience with PyTorch or TensorFlow.
• Proficient in Python and shell scripting.
• Experience with distributed systems and data pipelines.
• Strong ability to trade off features and scope.

Responsibilities

• Apply ML models to production use cases from design to deployment.
• Develop scalable, secure code shared across platforms.
• Contribute to backend systems and product improvements.
• Improve engineering standards, tooling, and security.
• Develop novel ML algorithms for large-scale use.
• Conduct metric-driven experiments to boost performance.
• Mentor and onboard junior ML engineers.
• Collaborate cross-functionally with other teams.

Skills

5+ years production ML

lead end-to-end development

data pipelines

ability to trade off features

secure coding practices

interpersonal skills

Education

Bachelor's Degree in Computer Science or related field

Tools

PyTorch

TensorFlow

Python

Shell scripting

Job description

About Deploy

Deploy is an intelligence infrastructure platform that gives developers and enterprises access to open source and proprietary AI models. For leading open source LLMs, Deploy operates an optimized model inference engine that keeps costs and latency low while maintaining high throughout. Deploy also offers a set of proprietary AI models that address challenges in content safety, AI & deepfake detection, sponsorship intelligence, and IP & publicity protection. Trusted by the world's largest and most innovative organizations, Deploy's solutions unlock high-performance AI model inference at production scale.
Deploy has raised more than $200M from leading investors, including Tomales Bay Capital, General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. The company has more than 250 employees across offices in San Francisco, Seattle, New York, and Delhi.

Senior Machine Learning Engineer

In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the forefront of deep learning technology, prototyping state-of-the-art neural net models and launching these models into production. We value hard workers who have no qualms working with terabyte-scale datasets, who are interested in learning new technologies at all levels of the machine learning stack, and who move fast and take ownership of their projects. Our ideal candidate has experience creating a working machine learning-powered project from the ground up, contributes innovative ideas and ingenious implementations to the team, and is capable of planning out scalable, maintainable data pipelines.

Responsibilities

• Everything involved in applying a ML model to a production use case, including, designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
• Write and maintain scalable, performant and secure code that can be shared across platforms
• Meaningfully contribute to the product and core backend systems by suggesting and executing improvements
• Improve engineering standards, tooling, processes and security
• Develop novel, accurate, and performant ML algorithms for use at scale
• Conduct metric-driven research experiments to improve model performance
• Provide mentorship to and help onboard junior ML engineers
• Collaborate cross-functionally with other teams
• Utilize OWASP top 10 techniques to secure code from vulnerabilities
• Maintain awareness of industry best practices for data maintenance handling as it relates to your role
• Adhere to policies, guidelines and procedures pertaining to the protection of information assets
• Report actual or suspected security and/or policy violations/breaches to an appropriate authority

Requirements

• You have a Bachelor's Degree in computer science or a related field
• You have a minimum of 5 years of building production scale ML models
• You know the ins and outs modern machine learning frameworks, such as PyTorch or Tensorflow
• You are an expert in scripting languages such as Python and/or shell scripts, particularly for data analysis
• You have experience writing code and training across distributed systems
• You have an ability to understand and make well-reasoned tradeoffs in designing features
• You can lead end to end development of new products
• You are very knowledgeable in at least one focus area of machine learning, such as computer vision or NLP
• You strongly believe in high code quality, automated testing, and other engineering best practices
• You have attention to detail and a passion for correctness
• You are comfortable with ambiguity and scoping solutions with your teammates
• You have strong interpersonal and communication skills with a bias towards action

Who We Are

We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Deploy, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company.

Thank you for your interest in Deploy and we hope to meet you soon!

The current expected base salary for this position ranges from $160,000 - $250,000. Actual compensation may vary depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here.