The Role
Leads and mentors machine learning engineers developing and deploying large-scale models. Partners with product, engineering, DevOps, labeling, sales, and recruiting teams to define roadmaps, deliver product milestones, and improve model quality. Oversees the full ML lifecycle, including data collection, labeling, experimentation, training, testing, deployment, security, and risk management. Contributes to technical architecture, modeling strategies, hiring, onboarding, and engineer development.
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.
Machine Learning Manager
In order to execute our vision, we're constantly growing our machine learning team. We are looking for an exceptional leader to help us with that growth, making sure that each engineer reaches their full potential. We value hard workers who have no qualms working with terabyte-scale datasets. We’re interested in experimenting with new models, new ideas, and training on novel datasets. Our ideal candidate has experience managing a team of machine learning engineers working on ML projects of a massive scale, contributes innovative ideas and ingenious modeling improvement strategies to the team, and is capable of mentoring junior engineers through their journey to become better.
Responsibilities
- Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting the long term vision of the team
- Lead a team of highly capable and passionate machine learning engineers, helping them achieve their goals through mentorship
- Participate in products technical design and architecture
- Participate in the full development cycle: data collection, labeling, model development, experimentation, training, testing, and deployment in production
- Drive delivery for our product milestones, continually releasing model with new well tested features and ensuring quality metrics are achieved
- Implement and manage security protocols such as training, code review, and best practices
- Own and manage the risk and security of your business function in coordination with the Security Team
- 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
- Undergraduate or graduate degree in computer science or similar technical field
- 4+ years experience as a machine learning engineer, with experience in training large deep learning models and working with real world data
- Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP
- 2+ years experience managing machine learning teams
- You have an ability to understand and make well-reasoned tradeoffs in designing features
- Management skills: ability to set roadmap and goals for a team and its individual members, delegate, mentor, and deliver results
- Have a desire to interview engineers, collaborate with a recruiting team, and smoothly onboarding new team members
- Have experience collaborating with product managers and labeling team in delivering model improvements
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 $180,000 - $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.
Skills Required
- Undergraduate or graduate degree in computer science or a similar technical field
- 4+ years of experience as a machine learning engineer
- Experience training large deep learning models and working with real-world data
- Knowledge of at least one machine learning focus area, such as computer vision, audio, or natural language processing
- 2+ years of experience managing machine learning teams
- Ability to understand and make well-reasoned feature design tradeoffs
- Ability to set team and individual roadmaps and goals, delegate, mentor, and deliver results
- Willingness to interview engineers, collaborate with recruiting, and onboard new team members
- Experience collaborating with product managers and labeling teams to deliver model improvements
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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.
