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Snorkel AI

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About

Snorkel AI provides a platform to build specialized AI with data and expertise. It unlocks the power of programmatic AI data development to build production AI applications with Snorkel Flow. It is used for LLM evaluation, Data labeling & annotation, LLM fine-tuning and RAG optimization. The Snorkel Flow AI data development platform provides data scientists and subject matter experts with a collaborative platform for capturing domain knowledge, using it to label entire datasets or generate synthetic ones, and to quickly iterate on training data and model development via built-in guided error analysis and model evaluation.

Platform
Web
Task
data labeling

Features

computer vision

llm evaluation

rag optimization

nlp applications

data labeling & annotation

llm fine-tuning & alignment

programmatic ai data development

ai data development platform

Job Opportunities

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Snorkel AI

Applied Machine Learning Engineer

Snorkel AI is an AI data development platform that enables users to build specialized AI with their data and expertise. It focuses on programmatic data development for AI, offering solutions for data labeling, RAG optimization, and LLM fine-tuning.

sciencehybridNew York
$140,000.00 - $200,000.00
full-time

Benefits:

  • comprehensive medical, dental, and vision plans

  • yearly wellness stipend

  • 401k program

  • parental leave program

  • workstation setup allowance

Experience Requirements:

  • 5+ years of professional experience with machine learning, or 2+ years of professional experience with machine learning with an advanced degree in a relevant field

  • 1+ year of professional experience working directly with external customers to scope out build machine learning models, tools, or services

  • Expertise in modern machine learning frameworks and technologies (e.g. PyTorch, Transformers, Scikit-learn, NumPy, Pandas), and an obsession with thorough ML evaluation

  • Experience building and maintaining large scale, production data pipelines for machine learning applications

  • Ability to work in a fast-paced environment and strong technical communication skills

Responsibilities:

  • Assist customers with the delivery of a Machine Learning project from beginning to end, including business case definition and scoping, data aggregation and exploration, algorithm selection, and model deployment to deliver business impact to the organization

  • Present findings and recommendations to customer stakeholders, assist with program ideation and technical program management, and brief materials.

  • Design, develop, and deploy enterprise AI/ML solutions across various industries like finance, healthcare, insurance, retail and more

  • Serve as the voice of our customers for new ML paradigms, data science workflows, and share customer feedback to product teams

Show more details

Machine Learning Customer Engineer

Snorkel AI is an AI data development platform that enables users to build specialized AI with their data and expertise. It focuses on programmatic data development for AI, offering solutions for data labeling, RAG optimization, and LLM fine-tuning.

engineeringremote
$120,000 - $160,000
full-time

Benefits:

  • comprehensive medical, dental, and vision plans

  • yearly wellness stipend

  • 401k program

  • parental leave program

  • workstation setup allowance

Education Requirements:

  • B.S. degree in a quantitative field such as Computer Science, Engineering, or comparable degree/experience.

Experience Requirements:

  • 2+ years experience working in a technical customer-facing role.

  • Proficient in Python.

  • Previous experience with cloud infrastructure providers such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform.

  • Outstanding organizational skills and ability to multitask in order to effectively prioritize and manage customer requests.

  • Experience with common support software like Zendesk, Jira, and Slack.

Responsibilities:

  • Partner with Snorkel Flow users to design, build, troubleshoot and deploy AI applications.

  • Lead the resolution of critical technical issues, providing prompt and complete resolution to technical challenges and business issues.

  • Perform live working sessions to analyze and address customer reported issues.

  • Prioritize, document and coordinate customer issues with account assigned ML Success Managers and the Snorkel engineering team.

  • Contribute to internal and external guides and docs, improving our self-service support materials.

Show more details

Machine Learning Customer Engineer

Snorkel AI is an AI data development platform that enables users to build specialized AI with their data and expertise. It focuses on programmatic data development for AI, offering solutions for data labeling, RAG optimization, and LLM fine-tuning.

Benefits:

  • comprehensive medical, dental, and vision plans

  • yearly wellness stipend

  • 401k program

  • parental leave program

  • workstation setup allowance

Education Requirements:

  • B.S. degree in a quantitative field such as Computer Science, Engineering, or comparable degree/experience.

Experience Requirements:

  • 2+ years experience working in a technical customer-facing role.

  • Proficient in Python.

  • Previous experience with cloud infrastructure providers such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform.

  • Outstanding organizational skills and ability to multitask in order to effectively prioritize and manage customer requests.

  • Experience with common support software like Zendesk, Jira, and Slack.

Responsibilities:

  • Partner with Snorkel Flow users to design, build, troubleshoot and deploy AI applications.

  • Lead the resolution of critical technical issues, providing prompt and complete resolution to technical challenges and business issues.

  • Perform live working sessions to analyze and address customer reported issues.

  • Prioritize, document and coordinate customer issues with account assigned ML Success Managers and the Snorkel engineering team.

  • Contribute to internal and external guides and docs, improving our self-service support materials.

Show more details

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