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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 ...

Kasmo Global

AI-ML Engineer

Battleboro, NC

Strong experience with PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, LightGBM. Hands-on experience with Generative AI, LLMs, RAG pipelines, and vector databases. Advanced knowledge of Docker ...

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 ...

Worthland

Lead Risk Manager, Payment Fraud

New York, NY · 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 ...

Tata Consultancy Service Limited

AI Engineer

Sunrise, FL · On-site

$100K - $130K/yr

NumPy, Pandas, Scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow, MLflow, Matplotlib • Generative & Agentic AI: LangChain, LangGraph, LlamaIndex, FAISS / Pinecone,OpenAI / Anthropic / Gemini ...

Epitec

Data Scientist

Southfield, MI · On-site

$128K/yr

Python, SQL, Scikit-learn, XGBoost, Prophet, ARIMA, RESTful APIs, GCP, Terraform, Docker, VBA, and ODBC. Will also accept any suitable combination of education, training, and/or experience. Employer ...

VHL Technologies

AIML Architect

Charlotte, NC · Hybrid

Expert-level proficiency in Python and ML frameworks (Scikit-learn, TensorFlow, PyTorch, H2O, XGBoost, etc.). * Strong hands-on experience with AWS SageMaker for architecting, training, tuning ...

Marencor

AI/ML Data Scientist

New York, NY · On-site

Train supervised and unsupervised models using Python ( XGBoost, LightGBM, sklearn, PyTorch ) * Conduct data profiling, feature engineering, model evaluation using stratified validation * Implement ...

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 ...

Objectways

Engineer III - CCaaS Data & AI Engineer

Sunrise, FL · On-site

$109K - $131K/yr

Knowledge of AI/ML technologies including TensorFlow, XGBoost, SARIMA, Prophet, and prompt engineering. * Experience with GCP services including BigQuery, Cloud Run, Pub/Sub, and Apigee. * Experience ...

New

Staffingine LLC

Artificial Intelligence Engineer

Bellevue, WA · On-site

$129K - $155K/yr

Experience with ML frameworks eg scikitlearn XGBoost TensorFlow PyTorch. * Strong knowledge of statistics experimental design and causal inference. * Handson experience with data visualization tools ...

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How much do xgboost jobs pay per hour?

As of Jun 18, 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.
AI Engineer

AI Engineer

Staffingine LLC

Phoenix, AZ • On-site

Contractor

Posted 23 days ago

Be an early applicant

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