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Machine learning engineer • berkeley ca
Machine Learning Engineer
HiveSan Francisco, California, United States- Promoted
Machine Learning Engineer
Goliath PartnersSan Francisco, California, United StatesMachine Learning Engineer
GoodfireSan Francisco, California, United StatesMachine Learning Engineer
ScribdSan Francisco, California, United States- Promoted
Machine Learning Engineer
VirtualVocationsOakland, California, United StatesMachine Learning Engineer
LightfieldSan Francisco, California, United States- Promoted
Machine Learning Engineer
AquabyteSan Francisco, CA, United StatesMachine Learning Engineer
SciforiumSan Francisco, California, United States- Promoted
Machine Learning Engineer
CanalsSan Francisco, California, United States- Promoted
Machine Learning Engineer
OpenReqSan Francisco, CA, United States- Promoted
Machine Learning Engineer
TrypulseSan Francisco, California, United States- Promoted
Machine Learning Engineer
Capital OneSan Francisco, California, United States- Promoted
Machine Learning Engineer
King River Capital GroupSan Francisco, CA, United StatesMachine Learning Engineer
BaselayerSan Francisco, California, United States- Promoted
Machine Learning Engineer
LMArenaSan Francisco, California, United StatesMachine Learning Engineer
KiddomSan Francisco, California, United States- Promoted
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Machine Learning Engineer
DeWinter GroupSan Francisco, California, United States- Promoted
Machine Learning Engineer
G2M TalentSan Francisco, California, United States- Promoted
Machine Learning Engineer
Apiphany CorporationSan Francisco, CA, United StatesThe average salary range is between $ 117,000 and $ 200,000 year , with the average salary hovering around $ 165,000 year .
- software development manager (from $ 220,000 to $ 273,000 year)
- nuclear medicine (from $ 153,470 to $ 250,984 year)
- veterinarian (from $ 115,000 to $ 250,000 year)
- python developer (from $ 135,000 to $ 244,125 year)
- office administrative assistant (from $ 47,840 to $ 243,900 year)
- vp of engineering (from $ 68,428 to $ 237,500 year)
- embedded systems engineer (from $ 133,875 to $ 222,134 year)
- product director (from $ 157,500 to $ 220,750 year)
- applications engineer (from $ 149,709 to $ 218,500 year)
- startup (from $ 136,250 to $ 216,250 year)
- Lansing, MI (from $ 114,400 to $ 241,000 year)
- Cedar Rapids, IA (from $ 131,250 to $ 240,706 year)
- Grand Rapids, MI (from $ 133,750 to $ 240,706 year)
- Kent, WA (from $ 109,500 to $ 238,773 year)
- Simi Valley, CA (from $ 145,000 to $ 235,450 year)
- Spokane Valley, WA (from $ 145,000 to $ 235,450 year)
- Sunnyvale, CA (from $ 154,550 to $ 230,000 year)
- Bellevue, WA (from $ 140,000 to $ 229,250 year)
- Wichita Falls, TX (from $ 159,200 to $ 226,625 year)
- Austin, TX (from $ 144,900 to $ 225,000 year)
The average salary range is between $ 124,693 and $ 200,000 year , with the average salary hovering around $ 154,997 year .
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Machine Learning Engineer
HiveSan Francisco, California, United States- Full-time
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.
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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
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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.