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Xgboost Jobs (NOW HIRING)

Staffingine LLC

AI Engineer

Phoenix, AZ · On-site

... XGBoost and PyTorch for model development and training Design and optimize data processing workflows using SQL and other pipeline tools Integrate and manage APIs to support AI applications and ...

Reveille Technologies

ML Ops Engineer

Concord, CA · On-site

Concord, California Strong proficiency in Java and Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch) Develop and maintain ML pipelines using tools like MLflow, Kubeflow ...

Merican

AI Observability Engineer

Charlotte, NC · On-site

Develop machine learning models using PyTorch, Scikit-learn, and XGBoost. * Build analytics dashboards and provide AI-driven insights to stakeholders. * Deploy containerized applications using Docker ...

Flexton Inc

Expert AI/ML Engineer

Oakland, CA · On-site

Experience with Python and common ML/data science libraries such as pandas, NumPy, scikit-learn, XGBoost, TensorFlow, PyTorch, or similar. Practical experience with MLOps concepts such as model ...

Flexton Inc

Expert AI/ML Engineer

Oakland, CA · On-site

Experience with Python and common ML/data science libraries such as pandas, NumPy, scikit-learn, XGBoost, TensorFlow, PyTorch, or similar. * Practical experience with MLOps concepts such as model ...

ADDSOURCE

Principal Consultant - AI/ML

Sugar Land, TX · On-site

Develop ensemble model strategies combining LSTM, Prophet, and XGBoost for improved prediction accuracy of latent capacity * Build automated model deployment workflows, training/evaluation pipelines ...

1 point system

Senior Data Scientist

New York, NY · Remote

Expertise in Python, SQL, and Spark, and a broad array of machine learning frameworks (Scikit-Learn, XGBoost, Tensorflow, PyTorch, MXNet, LLM, etc). * Experience in developing and deploying solutions ...

OKX

Sr Data Scientist, Risk Strategy

San Jose, CA · On-site

... GBM, XGBoost, LGBM, etc. • Advanced programming skills of statistical / analytical software (SQL, R, Python,etc.) • Successful track record of owning and driving large, complex data analysis ...

Jobtailor

Distinguished Data Scientist

California, MO · On-site

$180 - $260/hr

Deep expertise in ML algorithms including XGBoost, CatBoost, LightGBM, Random Forest, and AutoML * Deep learning expertise with PyTorch and transformer architectures * Production experience with NLP ...

New

Xforia, Inc.

Data Scientist

Pandas, Numpy, Matplotlib, Scikit-learn, LightGBM, XGBoost, OpenAI • Coursework: Data Mining, Data Visualization, Foundations of Analytics, Database Management, Web Analytics, Software Engineering ...

Worthland

Lead Risk Manager, Payment Fraud

Boston, MA · Hybrid

$150K - $180K/yr

Sklearn, XGBoost, LightGBM. * Mandarin Chinese fluency (the company operates a bilingual EN/CN working environment; this is a hard requirement). * Based in or willing to relocate to the Greater ...

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How much do xgboost jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for xgboost in the United States is $36.26, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $39.66 per hour, depending on experience, location, and employer.

What is XGBoost?

XGBoost stands for eXtreme Gradient Boosting and is an open-source machine learning library that provides an efficient and scalable implementation of gradient boosting algorithms. It is commonly used for supervised learning tasks, such as classification and regression, due to its high performance, speed, and ability to handle missing values. XGBoost supports parallel processing, regularization to prevent overfitting, and can be used with various programming languages like Python, R, and Julia. Its popularity stems from its success in many machine learning competitions and real-world applications.

What types of projects or datasets do professionals commonly work with when using XGBoost in a machine learning role?

Professionals using XGBoost often tackle projects involving structured data, such as customer analytics, credit scoring, fraud detection, and sales forecasting. XGBoost is particularly valued for its speed and accuracy with large tabular datasets, making it a popular choice in finance, healthcare, and e-commerce. On a daily basis, you may collaborate with data engineers to preprocess data, work with data scientists to tune hyperparameters, and communicate findings to business stakeholders. The role typically involves iterating on feature engineering, model evaluation, and integrating models into production pipelines.

What are the key skills and qualifications needed to thrive as a machine learning engineer specializing in XGBoost, and why are they important?

To thrive as a Machine Learning Engineer specializing in XGBoost, you need a strong background in statistics, data analysis, and programming (especially Python), often supported by a degree in computer science or a related field. Proficiency with XGBoost, data preprocessing libraries (like pandas and NumPy), and experience with machine learning platforms such as scikit-learn or TensorFlow are typically required. Analytical thinking, problem-solving, and effective communication are essential soft skills for interpreting results and collaborating with stakeholders. These skills ensure accurate model development, efficient implementation, and impactful business outcomes from machine learning projects.

What is the difference between Xgboost vs Data Scientist?

AspectXgboostData Scientist
Primary RoleDeveloping and tuning machine learning models, especially gradient boosting algorithmsAnalyzing data, building models, and deriving insights across various techniques
Required SkillsProgramming (Python, R), machine learning, data preprocessingStatistics, programming, data visualization, machine learning
Work EnvironmentData science teams, machine learning projects, software developmentResearch, data analysis, cross-functional collaboration

While Xgboost is a specific machine learning algorithm used within data science projects, a Data Scientist encompasses a broader role involving data analysis, modeling, and insights. Xgboost is a tool often employed by Data Scientists to improve predictive performance, but the Data Scientist's responsibilities extend beyond just implementing algorithms.

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Xgboost jobs near you
Infographic showing various Xgboost job openings in the United States as of August 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 100% In-person job distribution, with an average salary of $75,411 per year, or $36.3 per hour.

AI Engineer

Staffingine LLC

Phoenix, AZ • On-site

Contractor

Re-posted 25 days ago

Job description

Job Title: AI Engineer
Job Location: Phoenix, AZ
Job Type: Contract

Job Description:

  1. Develop and implement AI solutions using Python and AI frameworks such as Langgraph and Langchain Work with vector databases like Pinecone to manage and query highdimensional data Build and maintain machine learning pipelines for data processing and model deployment Utilize ML frameworks including XGBoost and PyTorch for model development and training Design and optimize data processing workflows using SQL and other pipeline tools Integrate and manage APIs to support AI applications and services Collaborate with crossfunctional teams to deliver scalable AIdriven products 

Roles and Responsibilities 

  1. Design develop and deploy AI and machine learning models using Python and relevant AI stacks Manage vector databases to enhance data retrieval and storage efficiency Build robust ML pipelines to automate data ingestion preprocessing and model training Apply advanced ML frameworks such as XGBoost and PyTorch for predictive analytics Develop data processing solutions involving SQL and pipeline orchestration Create and maintain APIs for seamless integration of AI components Collaborate with data scientists engineers and stakeholders to ensure project success Continuously monitor and improve AI system performance and scalability

Skills

Mandatory Skills : Agentic Framework