Staff Machine Learning Engineer

Hive; Seattle (WA); Hybrid; USD 200,000 - 300,000; Full time

Benefits offered by this job

Health insurance

Vision & Dental insurance

Gym membership

Job summary

Deploy seeks a Staff Machine Learning Engineer to advance production ML models, design scalable data pipelines, and deliver robust backend services. You will mentor teammates and collaborate across teams to shape the ML platform.

You should have deep experience in distributed systems, ML frameworks like PyTorch/TensorFlow, and Python scripting, with a track record of end-to-end product development in fast-paced environments.

Qualifications

• Bachelor's degree in computer science or related field.
• 8+ years of experience building web applications and distributed systems.
• Experience delivering scalable backend APIs.
• Expertise in ML frameworks (PyTorch or TensorFlow).
• Strong communication and leadership with ability to mentor teammates.
• Ability to lead end-to-end product development of new ML-powered solutions.

Responsibilities

• Apply ML models to production use cases including design, data gathering, training, and deployment.
• Write scalable, high-performance backend code shared across platforms.
• Contribute to core backend systems and product direction.
• Improve engineering standards, tooling, and processes.
• Develop novel ML algorithms for scale and performance.
• Conduct metric-driven experiments to improve model performance.
• Mentor ML engineers and onboard new team members.
• Lead cross-functional collaboration across teams.

Skills

Distributed systems

Backend APIs

Leadership

Mentorship

Communication

Model deployment

Education

Bachelor's Degree in CS or related

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.

Staff 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 code that can be shared across platforms
• Contribute meaningfully to the product and core backend systems by suggesting and executing improvements
• Improve engineering standards, tooling, and processes
• 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 ML engineers
• Lead cross-functional collaboration with other teams
• Contribute to defining strategic direction, planning the roadmap
• 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

Minimum Requirements

• You have a Bachelor's Degree in computer science or a related field
• You have 8+ years of experience building web applications
• You have successfully implemented highly-available distributed systems/microservices
• You have delivered scalable backend APIs
• You have strong interpersonal and communication skills with a bias towards action
• You have experience writing code and training across distributed systems
• You have the ability to understand and make well-reasoned tradeoffs in designing features
• You are an expert in 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 are a subject matter expert in at least one focus area of machine learning, such as computer vision or natural language processing
• You can lead end to end development of new products

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 $200,000 - $300,000. 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.

Employees are eligible to participate in a number of Company-sponsored benefits, including health, vision and dental insurance. Employees are also eligible to participate in a gym membership as part of our commitment to employee wellness. In addition, employees will be entitled to paid vacation in accordance with the Company's vacation policy.

Hired applicant may receive an equity grant in the form of an option to purchase stock in the future for a specified price.