The Role
Leads end-to-end machine learning development, including neural network design, data collection, model training, tuning, deployment, monitoring, and optimization at production scale. Builds scalable code and data pipelines, develops novel ML algorithms, improves backend systems and engineering processes, conducts metric-driven research, mentors engineers, and contributes to product strategy and roadmap planning.
Summary Generated by Built In
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.
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.
Skills Required
- 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
- 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 in feature design
- 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
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The Company
What We Do
Hive is the leading provider of cloud-based enterprise AI solutions to power the next wave of intelligent automation. The company offers a portfolio of best-in-class deep learning models, built with consensus-validated training data sourced and annotated by a distributed workforce of more than 2 million registered contributors. Hive's APIs enable use cases including automated content moderation, contextual advertising, advertising and sponsorship measurement, document parsing, and more. Hive processes billions of API requests per month for many of the world’s largest and most innovative companies. Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Jericho Capital, Bain & Company, Visa Ventures, and others. In April 2021, Hive announced a $50M Series D at a $2B valuation. The San Francisco-based company has 175+ full-time employees globally, in addition to a distributed workforce of more than 2 million global contributors that supports data labeling operations. For more information, visit thehive.ai.
