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Company

Original Job Post

Springboard · 2 days ago

Mentor - Machine Learning Career Track

United States

Part-time, Contract

Remote

Mid Level

$14.03/mo - $25.50/mo

3+ years exp

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E-LearningEdTech

Culture & Values

Hiring Manager

Rachel Rosen

Insider Connection @Springboard

Discover valuable connections within the company who might provide insights and potential referrals, giving your job application an inside edge.

Responsibilities

Provide 1-1 guidance to participants in the Machine Learning Engineering Career Track Bootcamp

Help students become proficient in Machine Learning Engineering through a curated online curriculum and project-based deliverables

Engage in biweekly 30-minute check-ins with students to discuss questions, projects, and career advice

Communicate with students outside of scheduled calls to support learning and career objectives

Critique work and provide meaningful feedback on machine learning engineering

Inspire and mentor students to successfully transition into machine learning engineering roles

Qualification

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PythonData WranglingPandasMatplotlibSeabornPEP 8SQLMachine LearningScikit-learnLinear RegressionLogistic RegressionDecision TreesClusteringAWSGCPAzureDeep LearningComputer VisionNatural Language ProcessingTensorFlowPyTorchCloud MLGenerative AIModel VersioningReproducibilityProblem-SolvingCommunicationEmpathyCritical ThinkingAI

Required

3+ years of industry experience in machine learning engineering or data science

Experience in Python Data Science Stack; using python and its standard libraries; building visualizations with Matplotlib and Seaborn; Writing code in Python using PEP 8 Standard

Data Wrangling: Use Pandas to wrangle and clean data; working with different file formats, from plain text, to CSV, to JSON; relational and non-relational databases; SQL

Machine Learning: Scikit-learn; ML techniques: linear and logistic regression, trees, and clustering

Deploying ML: Experience deploying ML solutions with a cloud service provider (at least one of AWS, GCP or Azure)

Deep Learning Fundamentals: Familiarity with deep learning, computer vision, natural language processing

Expertise in Python, libraries like TensorFlow and PyTorch, SQL, cloud ML, etc.

Experience working with large language models and generative AI, such as training and fine-tuning language models for specific tasks

Knowledge of cloud-based deployment strategies for large AI models and practical experience with model versioning and reproducibility

Have experience critiquing work, in particular giving meaningful feedback on machine learning engineering and are able to think on your feet quickly

Are empathetic and have excellent communication skills