Quick overview
SeniorityMid Senior
Employment typeFull Time
Work modeOn Site
LocationSan Francisco, United States
Deep LearningMachine Learning
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.
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.
Similar jobs
- OP

Machine Learning Performance EngineerRecently posted Auto Apply
Optiver · New York · Hybrid 🇺🇸
CUDADeep LearningC+++5Technology$200k/yr - HA
Senior Machine Learning EngineerRecently posted Auto Apply
Hum Ai · San Francisco · Hybrid 🇺🇸
FirebaseAWSPyTorch+3TechnologySalary not listed - GL

Machine Learning Engineer, Enterprise BrainRecently posted Auto Apply
Glean · Mountain View · Hybrid 🇺🇸
GitGDPRLLM+5Technology$200k - $280k/yr - CL

Coding RL EngineerRecently posted Auto Apply
Clera · San Francisco · On-site 🇺🇸
DockerRustJava+2EngineeringSalary not listed - CH

Senior Machine Learning EngineerRecently posted Auto Apply
Checkr · Denver · Hybrid 🇺🇸
RecruitingRubyApache Spark+12TechnologySalary not listed - BU

Reinforcement Learning EngineerRecently posted Auto Apply
Bugcrowd · Remote - US · Remote 🇺🇸
DockerRustGit+7EngineeringSalary not listed - BO

Machine Learning Engineer III, ShieldRecently posted Auto Apply
Box · Redwood City · Hybrid 🇺🇸
GCPScalaApache Spark+11Technology$175.5k - $219.5k/yr - AX

Senior Machine Learning Engineer IRecently posted Auto Apply
Axon · Seattle · Hybrid 🇺🇸
GCPAWSLLM+6Technology$150.8k - $241.2k/yr - AL

Sr. AI/ML Engineer (US)Recently posted Auto Apply
AlertMedia · Remote · Remote 🇺🇸
NLPScikit-learnA/B Testing+10TechnologySalary not listed - SK

Autonomy Engineer Intern, Reinforcement Learning, 2027 (HQ)Recently posted Auto Apply
Skydio · San Mateo · On-site 🇺🇸
DroneRoboticsCUDA+5EngineeringSalary not listed - LI

Senior Applied ML/AI EngineerRecently posted Auto Apply
Legion Intelligence · United States · Hybrid 🇺🇸
OracleMLOpsNLP+2Technology$200k - $240k/yr - SA

Machine Learning Scientist - Molecular Force FieldsRecently posted Auto Apply
Sandboxaq · United States · Remote 🇺🇸
PyTorchPythonMachine LearningTechnologySalary not listed