Hive logo

Machine Learning Engineer

Hive

San Francisco, CAFull-time$120–180K/yrPosted 5y agoStill listed 2 days ago

Most applications go out cold — see where you stand first. No sign-up to start.

Watch jobs like this.

At a glance

Compensation
$120–180K/yr
Location
San Francisco, CA
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Requirements

Credentials this posting asks for.

Bachelor's degree

Job overview

Hive is hiring a Machine Learning Engineer. Hive, a fast‑growing AI startup in San Francisco, seeks machine learning engineers who excel at prototyping state‑of‑the‑art neural networks and deploying them at scale. Candidates should thrive on terabyte‑scale datasets, quickly adopt new technologies across the ML stack, and take ownership of end‑to‑end production projects.

Key focus areas include Apply ML model to production, design and code neural networks, gather and refine data, train, tune, deploy at scale, and analyze results to improve accuracy and speed, Interface closely with Backend and DevOps teams as well as internal data labeling services, and Utilize OWASP top 10 techniques to secure code from vulnerabilities.

Successful candidates bring Undergraduate Or Graduate Degree In Computer Science Or Similar Technical Field, Significant Coursework In Mathematics Or Statistics, and 1-2 Years Industry Machine Learning Experience. Important skills include Deep Learning Technology, Neural Net Models Prototyping, Launching Models Into Production, Working With Terabyte-Scale Datasets, Learning New Technologies, and Creating Machine Learning-Powered Project. Preferred (not required): Neural Net Models.

Skills & qualifications

RequiredNice to have

Skills

Deep Learning TechnologyNeural Net Models PrototypingLaunching Models Into ProductionWorking With Terabyte-Scale DatasetsLearning New TechnologiesCreating Machine Learning-Powered ProjectInnovative IdeasIngenious ImplementationsPlanning Scalable Data PipelinesMaintainable Data PipelinesDesigning Neural NetworkCoding Neural NetworkGathering DataRefining DataTraining ModelTuning ModelDeploying at ScaleHigh ThroughputUptimeAnalyzing ResultsContinuously Update AccuracyContinuously Improve SpeedInterface With Backend TeamsInterface With DevOps TeamsInterface With Internal Data Labeling ServicesOWASP Top 10 TechniquesSecure Code From VulnerabilitiesIndustry Best Practices for Data Maintenance HandlingAdhere to PoliciesAdhere to GuidelinesAdhere to ProceduresProtection of Information AssetsReport Security ViolationsReport Policy ViolationsTensorFlowCaffePyTorchPythonQuickly Coding Data PipelinesPrototyping Data PipelinesNode.jsBashLinux Command-Line ToolsLarge DatasetsLatest Deep Neural Net ResearchLatest Deep Neural Net ArchitecturesUnderstanding TheoryUnderstanding MotivationsImplementing in ML FrameworkCommunication SkillsMachine LearningData Maintenance HandlingC++Scala/SparkSQLCassandraDockerDeep Neural Net ResearchCommunicationTeam PlayerNeural Net Models

Qualifications

Undergraduate or Graduate Degree in Computer Science or Similar Technical FieldSignificant Coursework in Mathematics or Statistics1-2 Years Industry Machine Learning ExperienceSuccessfully Trained and Deployed a Deep Learning Machine Model

Full job description

About Hive Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive’s solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more. Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI! Machine Learning Role 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
  • Interface closely with the Backend and DevOps teams as well as with our internal data labeling services
  • 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 an undergraduate or graduate degree in computer science or similar technical field, with significant coursework in mathematics or statistics
  • You have 1-2 years industry machine learning experience
  • You have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a personal project
  • You have strong experience with a high-level machine learning frameworks such as Tensorflow, Caffe, or Torch, and familiarity with the others
  • You know the ins and outs of Python, especially as it applies to the above ML frameworks
  • You are capable of quickly coding and prototyping data pipelines involving any combination of Python, Node, bash, and linux command-line tools, especially when applied to large datasets consisting of millions of files
  • You have a working knowledge of the following technologies, or are not afraid of picking it up on the fly: C++, Scala/Spark, SQL, Cassandra, Docker
  • You are up-to-date on the latest deep neural net research and architectures, both in understanding the theory and motivations behind the techniques, as well as how to implement them in the ML framework of your choice
  • You have great communication skills and ability to work with others
  • You are a strong team player, with a do-whatever-it-takes attitude Who We Are We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Hive, 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 Hive and we hope to meet you soon! The current expected base salary for this position ranges from $120,000 - $180,000. 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.

Similar jobs, posted recently

Open roles like this one, listed in the last 30 days.

You've read the whole posting — now see how you match it.