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Xgboost Jobs (NOW HIRING)

Roberts Recruiting

Senior Data Scientist

Boston, MA · On-site

Familiarity with Python NLP frameworks and libraries such as scikit, NumPy, and XGBoost * Experience working with engineers on algorithm development, architecture planning, and development

Raas Infotek LLC

AI/ML Engineer

Austin, TX

$113K - $136K/yr

Hands-on experience with Python, TensorFlow, PyTorch, Scikit-learn, Keras, and XGBoost. * Experience with Vector Databases (Pinecone, Weaviate, Chroma, FAISS). * Knowledge of MLOps tools (MLflow ...

New

Lorven Technologies

ML Ops Engineer

Concord, CA · On-site

Strong proficiency in Java and Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch). Experience with cloud platforms and containerization (Docker, Kubernetes). Familiarity ...

Steampunk

Data Scientist

Mclean, VA

$125K - $160K/yr

Develop machine learning models using frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar libraries. * Perform feature engineering, dataset preparation, and model optimization ...

Prophecy Technologies

Data Scientist

Atlanta, GA · On-site

Develop and deploy models using algorithms like Linear & Logistic Regression, SVM, Decision Trees, XGBoost, Hist Gradient Boosting, and LightGBM. * Utilize cloud technologies (AWS, Azure, Hadoop) for ...

TAO Digital Solutions

Senior ML Engineer

Indianapolis, IN

$99K - $137K/yr

Proficiency in Python, SQL, and ML frameworks (Scikit-Learn, XGBoost, TensorFlow). * Excellent communication skills for presenting insights to technical and business stakeholders. Preferred Skills

Advance Auto Parts, Inc.

Data Scientist

Raleigh, NC · On-site

Apply advanced techniques such as structural time series modeling and boosting algorithms (e.g., XGBoost, LightGBM). * Train and Tune Models: Develop and tune machine learning models using Python ...

Salesforce

DS with GEN AI

Murphy, TX · On-site

$14.25 - $18.50/hr

... XGBoost, Linear Regression, Clustering, Decicion Tree, KNN, SVN, etc. • LangChain & LangGraph: Hands-on experience building, deploying, and maintaining applications using LangChain and LangGraph ...

Salesforce

DS with GEN AI

Plano, TX · On-site

$14.25 - $18.50/hr

... XGBoost, Linear Regression, Clustering, Decicion Tree, KNN, SVN, etc. • LangChain & LangGraph: Hands-on experience building, deploying, and maintaining applications using LangChain and LangGraph ...

Steampunk

Data Scientist

Mclean, VA · On-site

$125K - $160K/yr

Develop machine learning models using frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar libraries. * Perform feature engineering, dataset preparation, and model optimization ...

GDIT

Senior Data Scientist

Concord, NC

Design, train, and validate supervised, unsupervised, and deep learning models using open-source libraries (PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM) to support forecasting ...

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How much do xgboost jobs pay per hour?

As of Jun 19, 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 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 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 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.

What is the highest paid job in data science?

In data science, senior roles such as Lead Data Scientist, Machine Learning Engineer, or Data Science Director tend to have the highest salaries, often exceeding six figures annually. These positions typically require advanced skills in machine learning, statistical analysis, and experience with tools like XGBoost, along with leadership responsibilities.

Is XGBoost better than linear regression?

XGBoost is a powerful machine learning algorithm that often outperforms linear regression in predictive accuracy, especially with complex, non-linear data. However, linear regression is simpler, more interpretable, and suitable for problems with linear relationships, making the choice dependent on the specific task and data characteristics in a data science or machine learning role.

Is XGBoost considered AI?

XGBoost is a machine learning algorithm used for classification and regression tasks, often employed by data scientists and machine learning engineers. While it is a tool within artificial intelligence applications, XGBoost itself is not considered AI but a method used to develop AI models. Knowledge of programming languages like Python or R and understanding of data preprocessing are important for roles involving XGBoost.

What does XGBoost stand for?

XGBoost is an open-source machine learning library that implements gradient boosting algorithms, commonly used for structured data prediction tasks. The name stands for eXtreme Gradient Boosting, highlighting its focus on high-performance gradient boosting techniques often utilized by data scientists and machine learning engineers.
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Xgboost jobs near you
Infographic showing various Xgboost job openings in the United States as of June 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $75,411 per year, or $36.3 per hour.

Remote Machine Learning Engineer

Angenex

Jersey City, NJ • Remote

Other

Posted 23 days ago

Job description

Remote Machine Learning Engineer

Jersey City, NJ, United States

About the Job

We're seeking an outstanding ML Engineer to join our data team and help build out best-in-class machine learning solutions on our platform, powering innovative solutions in marketing & sales and commercial analytics.

Responsibilities

- Build and deploy the ML pipelines that power the company machine learning platform.

- Manage MLOps infrastructure to monitor and optimize models.

Qualifications

Experience:

1+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist.

Proficiency across topics in machine learning and statistics.

Fluency in Python coding as well as data manipulation (SQL, Spark, Pandas)

Broad familiarity with the Python ecosystem and common libraries including Scikit-Learn, XGBoost, PyTorch, Keras, Tensorflow, Pandas, and common ML cloud services.

Familiarity with CNNs, RNN, LSTMs, and the latest research trends.

Experience implementing, deploying, and maintaining production machine learning systems.

Experience monitoring and optimizing model performance.

Experience with Linux, Docker and AWS, and basic development operations.

Advanced degree in computer science, mathematics, statistics or related area of study strongly preferred.

Apply