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H2O.ai

No-code AutoML platform for AI/ML

Senior Customer Data Scientist 1

Applied Machine LearningPosted on Nov 13
Full-timeMexico City, CDMX, MexicoNo salary listedIn-person

About the Job

Requirements

  • Proven experience in data science, machine learning, and artificial intelligence, with at least 4 years of hands-on experience.
  • Experience solving machine learning problems using H2O products is a plus, along with Python and R.
  • Knowledge and experience using machine learning techniques including supervised and unsupervised learning, clustering, decision tree learning, and neural networks, including their practical advantages, drawbacks, and tuning techniques.
  • Knowledge and experience using advanced statistical techniques and concepts, including regression, properties of distributions, and statistical tests and their proper usage.
  • Hands-on experience designing, training, and tuning neural networks using frameworks such as PyTorch, TensorFlow, or Keras.
  • Experience working with image data and pretrained image backbones such as ResNet, EfficientNet, ConvNeXt, and Vision Transformers for image classification, object detection, or segmentation, including transfer learning, fine-tuning, data augmentation, and GPU-based training.
  • Knowledge and experience in statistical and data mining techniques, including generalized linear models and regression, Random Forest, boosting, trees, text mining, and social network analysis.
  • Experience visualizing and presenting exploratory data analysis to stakeholders using H2O Wave, which is a plus, other standard data visualization libraries in Python and R, or Tableau or Power BI.
  • Understanding and experience with post-production model monitoring concepts and tools such as H2O ML Ops, which is a plus, and MLflow.
  • In-depth understanding of machine learning algorithms and experience applying generative AI and machine learning to solve real-world problems, including deploying end-to-end machine learning pipelines.
  • Interest in generative AI and large language models, including prompt engineering, retrieval-augmented generation, LLMOps, custom large language model creation, fine-tuning, and guardrails.
  • Ability to work independently and as part of a team.
  • Communication and presentation skills to convey complex technical concepts to non-technical stakeholders.

Responsibilities

  • Deliver data science and/or machine learning professional services to customers by working with cross-functional teams to gather requirements, preprocess and analyze data, and develop data-driven solutions.
  • Support customers in building custom data models, transformations, scorers, optimization loss functions, and metrics that can be leveraged with H2O Driverless AI to improve training performance for customer use cases and domains.
  • Build, train, and fine-tune neural network models for customer image-data use cases, leveraging pretrained image backbones to deliver accurate and efficient computer vision solutions.
  • Design and run customer training sessions on data science concepts and H2O products for audiences with varying data science skills and abilities.
  • Help customers understand data science, expert settings in H2O Driverless AI and H2O open source, and experiment-tuning strategies for incrementally improving model performance.
  • Explain model performance, interpretability, and post-deployment model-monitoring concepts so customers can make informed decisions based on model predictions.
  • Participate in developing machine learning solutions and artificial intelligence applications for internal use, contributing to the technology stack.

About the Company

H2O.ai

No-code AutoML platform for AI/ML

H2O.ai provides AI and ML solutions for businesses, with Driverless AI as its core AutoML platform. It automates feature engineering, model building, visualization, and interpretability to help users create predictive and generative models with minimal coding. The platform supports information retrieval, data labeling and processing, no-code deep learning, and emphasizes data security, plus a platform to develop, deploy, and share trusted AI apps. Its goal is to help organizations of all sizes accelerate data-driven decisions and scale secure AI deployment, differentiating through accessible AutoML, enterprise-grade security, and a strong talent base that includes Kaggle Grandmasters.

Company size
201-500
Company stage
Series E
Total funding
$251.1M
Headquarters
Mountain View, CA
Founded
2012

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