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Python developer Empleos en Edinburg tx

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Python developer • edinburg tx

Última actualización: hace 2 días

Remote Machine Learning Engineer Expert - AI Trainer ($90-$90 per hour)

MercorEdinburg, Texas, US
90,00 US$ por hora
Teletrabajo
A tiempo completo

Role Overview** We’re hiring experienced Machine Learning Engineers and Applied ML Researchers to design, solve, and evaluate complex machine learning challenges that reflect real-world ML workflow... Mostrar más

Remote CUDA Engineering Expert - AI Trainer ($80-$120 per hour)

MercorMcAllen, Texas, US
80,00 US$ por hora
Teletrabajo
A tiempo completo

Role Overview** Mercor is seeking GPU kernel optimization experts to contribute to a project with a leading AI lab.This opportunity is designed for freelancers with strong C++ skills, practical GPU... Mostrar más

Remote Software Developer $60 - $120/hourpay

Micro1McAllen, Texas, US
60,00 US$ por hora
Teletrabajo
A tiempo completo

Real-world expertise is turned into training data, evaluations, and feedback loops that improve how models perform.AI labs and enterprises use micro1 to train models and build reliable AI agents th... Mostrar más

Remote Legal Expert — Specialist (Real Estate, Tax, Bankruptcy, Estates) - AI Trainer ($100-$150

MercorPharr, Texas, US
Teletrabajo
A tiempo completo

About the Role Mercor is partnering with a leading AI lab to train frontier models on high-quality legal reasoning data.We're hiring Specialist Lawyers in Real Estate, Tax, Bankruptcy/Restructuring... Mostrar más

Remote Research Physics Expert - AI Trainer ($80-$140 per hour)

MercorPharr, Texas, US
80,00 US$ por hora
Teletrabajo
A tiempo completo

Role Overview We are seeking expert physics researchers to author and verify golden reference solutions for the **CritPt benchmark (arXiv:2509.Participants will solve CritPt research-level problems... Mostrar más

Remote Machine Learning Engineer Talent Network - AI Trainer ($70-$250 per hour)

MercorMcAllen, Texas, US
70,00 US$ por hora
Teletrabajo
A tiempo parcial

About Mercor’s talent network** Join our Machine Learning Engineer Expert Network to connect with leading AI labs and companies seeking your expertise.This is an open application for future contrac... Mostrar más

Part-Time Assistant Manager - Level 2

Hot TopicMcallen, TX, United States
A tiempo parcial

Part-Time Assistant Manager Level 2.At BoxLunch, we're committed using our love of pop culture to do something amazing: eliminate hunger.With every $10 spent, we donate a meal to Feeding America t... Mostrar más

Purchaser III or IV - Procurement Division

Texas Department of TransportationPharr, TX, United States
42.976,00 US$ anual
A tiempo completo +2

Purchaser III or IV - Procurement Division.Are you interested in putting your mind to work, solving problems for diverse stakeholders, and turning requests and plans into concrete detail on paper? ... Mostrar más

Remote Machine Learning Engineer Expert - AI Trainer ($90-$90 per hour)

Remote Machine Learning Engineer Expert - AI Trainer ($90-$90 per hour)

MercorEdinburg, Texas, US
Hace 2 días
Salario
90,00 US$ por hora
Tipo de contrato
  • A tiempo completo
  • Teletrabajo
Descripción del trabajo
# **1\. Role Overview** We’re hiring experienced Machine Learning Engineers and Applied ML Researchers to design, solve, and evaluate complex machine learning challenges that reflect real-world ML workflows. This role requires strong hands-on modeling expertise, the ability to develop high-quality reference solutions, and deep familiarity with modern machine learning techniques across a variety of domains and data modalities. # **2\. What You’ll Do** - Develop end-to-end machine le.arning solutions for challenging prediction and modeling problems - Analyze datasets and define appropriate modeling approaches, validation strategies, and evaluation metrics - Perform exploratory data analysis, feature engineering, and data preprocessing - Train, tune, and evaluate machine learning models across tabular, text, image, and time-series datasets - Develop strong reference solutions using industry-standard machine learning techniques and best practices - Review and validate the technical quality of machine learning projects and deliverables - Document methodologies, assumptions, and evaluation results in a clear and reproducible manner - Identify opportunities to improve model performance through systematic experimentation and iteration # **3\. Required Qualifications** - Master’s degree or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Electrical Engineering, or a related field from a top-tier university - 2+ years of hands-on experience developing, training, evaluating, and optimizing machine learning models in a professional or research setting. - Strong proficiency in Python and modern machine learning frameworks (e.g., scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow) - Demonstrated experience building end-to-end machine learning solutions, including data preparation, model development, validation, and evaluation - Strong understanding of model evaluation metrics, validation methodologies, and experimental design - Experience with one or more of the following areas: - Tabular machine learning - Natural language processing - Computer vision - Recommendation systems - Ranking systems - Time-series forecasting - Ability to work independently on open-ended machine learning problems and deliver high-quality technical outputs # **4\. Preferred Qualifications** - PhD from a leading research university - Experience at leading technology companies, AI labs, research institutions, or high-growth startups - Participation in competitive machine learning or data science competitions - Experience optimizing models against performance-based evaluation metrics - Familiarity with advanced techniques such as ensembling, hyperparameter optimization, transfer learning, foundation model fine-tuning, or reinforcement learning - Publications, patents, or significant open-source contributions in machine learning or AI - Experience reviewing, mentoring, or evaluating the work of other machine learning practitioners