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Probably Genetic
San Francisco, CA, United States
About Probably Genetic: Probably Genetic is changing the lives of patients living with severe, complex diseases. Our data platform is used by drug developers and patient advocacy groups to develop and launch treatments for these patients. Our technology discovers undiagnosed patients online, analyzes their disease state using machine learning and a
Job Source: Probably GeneticCrowdAI
San Francisco, CA, United States
[Full Time] Machine Learning Engineer at CrowdAI (United States) | BEAMSTART Jobs Machine Learning Engineer CrowdAI United States Date Posted 26 Jun, 2022 Work Location San Francisco, United States Salary Offered Not Specified Job Type Full Time Experience Required 3+ years Remote Work Yes Stock Options Yes Vacancies 1 available Apply online:
Job Source: CrowdAIQuinStreet
Foster City, CA, United States
Job Description Job Description Powering Performance Marketplaces in Digital Media QuinStreet is a pioneer in powering decentralized online marketplaces that match searchers and "research and compare" consumers with brands . We run these virtual- and private-label marketplaces in one of the nation's largest media networks. Our industry leading
Job Source: QuinStreetKuraray America, Inc.
San Mateo, CA, United States
The Role: We are seeking a self-motivated, experienced Machine Learning Engineer* to develop, deploy, and refine tools to accelerate our antibody design cycle. *At BigHat we believe in titles that are commensurate with skill set, relative organizational impact, and value contribution; more experienced candidates are encouraged to apply, with
Job Source: Kuraray America, Inc.Proprius
San Francisco, CA, United States
Machine Learning Engineer Location: San Francisco, CA Sponsorship: No Relocation: No Industry: Machine Learning Join an artificial intelligence company in San Francisco that excels at visual recognition and is looking for a new ML engineer to join their team. Become part of a collaborative team that tackles research problems through a process
Job Source: PropriusNtropy
San Francisco, CA, United States
While significantly more efficient than humans for many tasks, the cost and latency of LLMs is still prohibitive for most real world applications. At Ntropy, our mission is to make LLMs viable at scale. We are developing a new kind of domain-specific wrappers for language models, that leads to a reduction in the number of queries to the base model
Job Source: NtropyShipt
San Francisco, CA, United States
Shipt, Inc. seeks a full-time Machine Learning Engineer based in San Francisco, CA. This role will drive the development and deployment of key AI initiatives (e.g., personalization, price optimization, promotion optimization, and ad tech platform) and services (e.g., quality, efficiency, security, and affordability). This position requires a Master
Job Source: ShiptSkale Talent
San Francisco, CA, United States
We’re partnering with a leading autonomous driving company in San Francisco who are looking for a Senior Machine Learning Engineer to join their team. They are working on a scalable highway autonomy product for the consumer car market. Working directly with several OEM partners, they’re building an end-to-end solution to L4 autonomy, seamlessly int
Job Source: Skale TalentSan Francisco, CA, United States
Perplexity is building the next generation answer engine, empowering our users to find information in new and more effective ways. Perplexity applies LLMs for knowledge search at scale, serving millions of users across the world. In pursuit of this mission, we are looking for engineers to build recommendation systems for a more engaging, easier to use product. You will be part of a dynamic team dedicated to pushing the boundaries of what's possible with machine learning, particularly in the realms of content discovery and personalization.
Our current backend stack is Python, Rust, TensorRT-LLM, Kubernetes, AWS. You will work on designing and implementing machine learning models that drive our recommendation systems, retrieval algorithms, and classifiers.
Responsibilities
Develop, train, and optimize machine learning models for recommendation systems.
Build groundwork infrastructure for retrieval.
Work with real world data to create scalable feedback loops.
Incorporate state of the art LLMs into traditional machine learning systems.
Qualifications
Experience with machine learning at scale.
Experience with retrieval infrastructure.
Creative problem-solving skills with an ability to explore a new landscape of models.
Eagerness to build from 0 to 1 and unlock potential in new products.
Familiarity with big data pipelines for feature engineering.
At least 6 years of experience with machine learning and backend engineering.
The cash compensation for this role is $200,000 to $250,000.
Since publicly launching the world’s first fully functional conversational answer engine a year ago, we’ve grown to 10 million monthly active users and have served over half a billion queries in 2023.To support our rapid consumer adoption and expansion plans, we’ve raised $73.6 million in Series B funding from trusted VC firms and prominent tech visionaries. IVP led the round with continued support from our Seed and Series A investors NEA, Elad Gil, Nat Friedman, and Databricks, as well as new investors NVIDIA, Jeff Bezos (through Bezos Expeditions Fund), Tobi Lutke, Bessemer Venture Partners, Naval Ravikant, Balaji Srinivasan, Guillermo Rauch, Austen Allred, Factorial Funds, and Kindred Ventures, among others. Building upon our Series A earlier this year, we’ve now raised $100 million to date.
Final offer amounts are determined by multiple factors, including, experience and expertise, and may vary from the amounts listed above.
Equity: In addition to the base salary, equity is part of the total compensation package.
Benefits: Comprehensive health, dental, and vision insurance for you and your dependents. Includes a 401(k) plan.
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Email Alert for Machine Learning Engineer jobs in San Francisco, CA, United States
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