Machine Learning Engineer, Otter - San Francisco at Otter

San Francisco, California, United States

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Not SpecifiedCompensation

Junior (1 to 2 years)Experience Level

Full TimeJob Type

UnknownVisa

Software, Food DeliveryIndustries

Requirements

Candidates should possess an advanced degree (PhD or Master's) in Computer Science, Machine Learning, Data Mining, Statistics, or a related technical field, with a preference for 3+ years of relevant experience. Required skills include deep knowledge and experience with at least one ML model such as LLMs, GNN, Deep Learning, Logistic Regression, or Gradient Boosting trees. Proficiency in Python is essential, with familiarity in Java/Go. Experience with data analysis, visualization, generative AI, data mining, information retrieval, advanced statistics, natural language processing, or computer vision is also necessary. Strong communication and presentation skills, along with the ability to design and create long-lasting architecture, are expected.

Responsibilities

The Machine Learning Engineer will leverage cutting-edge machine learning and statistical methodologies, including LLMs, deep learning, and graph neural networks, to solve challenges in AI agents, order logistics prediction and optimization, robotics automation, recommendation systems, and knowledge graph building and mining. Responsibilities include developing and deploying robust applied machine learning solutions in production, creating onboarding codelabs, tools, and infrastructure to democratize ML resources, and collaborating closely with a team to enhance and support technology. The role also involves driving innovation within the team and supporting technological advancements.

Skills

Machine Learning

Statistical Modeling

Large Language Models (LLMs)

Deep Learning

Graph Neural Networks

Logistic Regression

Gradient Boosting

AI Agents

Order Logistics Prediction

Recommendation Systems

Knowledge Graph Building

Robotics Automation

Otter

Connects parents with vetted babysitters

About Otter

Otter connects parents with qualified babysitters through its online platform, focusing on the childcare industry. The service stands out due to its thorough vetting process for sitters, which includes skills tests, reference checks, and interviews, along with mandatory background checks for both parents and sitters to ensure safety. Parents can book a sitter on short notice, sometimes as little as two hours, making it a convenient option for last-minute childcare needs. The company earns revenue by charging a fee for each booking, which is shared with the sitters, providing them with a flexible income opportunity. With significant backing from prominent venture capital firms, Otter aims to address the demand for reliable childcare services while ensuring a safe environment for families.

San Francisco, CaliforniaHeadquarters

2020Year Founded

$30MTotal Funding

SERIES_ACompany Stage

Social Impact, Consumer GoodsIndustries

1-10Employees

Risks

Increased competition from new platforms offering similar services at lower fees.

Changes in local regulations could increase operational costs and complicate compliance.

Rising concerns about data privacy and security could decrease user trust.

Differentiation

Otter offers a rigorous vetting process for sitters, ensuring safety and reliability.

The platform allows parents to book childcare with as little as two hours' notice.

Otter connects parents with local stay-at-home parents, fostering community-based childcare.

Upsides

Increased demand for flexible childcare solutions due to remote work trends.

Growing interest in last-minute booking options for childcare services.

Venture capital interest indicates strong growth potential for tech-enabled childcare solutions.

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