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Jobs(26,646)/Machine Learning Engineer Role(342)/Wynd Labs (1) - Machine Learning Engineer
Wynd Labs

Wynd Labs - Machine Learning Engineer

Remote - United States+ Equity7mo ago
RemoteMidNAArtificial IntelligenceData AnalyticsMachine Learning EngineerPythonLearning & DevelopmentDocumentationhypothesisData Quality

Requirements

• Bachelor’s, Master’s, or Doctoral degree in Data Science, Computer Science, Statistics, or a related field. • A minimum of 3 years of work or research experience dealing with large datasets. • Strong coding skills in Python or other object-oriented programming languages. • Graduate-level knowledge of statistics, including but not limited to hypothesis testing, regression analysis, and probability. • Excellent work ethic and the ability to thrive in a fast-paced startup environment. • Strong problem-solving skills and attention to detail. • Good communication skills, with the ability to articulate complex data concepts to non-technical stakeholders. • Experience working in a high output team.

Responsibilities

• Developing, fine-tuning, and deploying LLMs for various NLP tasks such as text generation, summarization, translation, and sentiment analysis. • Designing and implementing pipelines for processing and analyzing large datasets. • Analyzing and interpreting complex time series data to provide actionable insights and solutions. • Designing, implementing, and maintaining data-driven models and algorithms. • Collaborating with cross-functional teams to understand data needs and deliver timely solutions. • Ensuring data quality and integrity throughout all processes. • Utilizing Optical Character Recognition (OCR) technology to convert different types of documents into editable and searchable data. • Continuously researching and implementing best practices in data science and machine learning. • Contributing to the development and improvement of internal data processing tools and infrastructure.

Benefits

• Opportunity. We are at at the forefront of developing a web-scale crawler and knowledge graph that allows ordinary people to participate in the process, and share in the benefits of AI development. • Culture. We’re a lean team working together to achieve a very ambitious goal of improving access to public web data and distributing the value of AI to the people. We prioritize low ego and high output. • Compensation. You’ll receive a competitive salary, benefits and equity package.

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