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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 ...

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 ...

Merican Inc

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 ...

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 ...

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 ...

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 ...

ClifyX

AI ML Data Scientist

Cary, NC · On-site

... XGBoost-in various business problems (AML, fraud detection, mortgage default, foreclosure, credit risk management, price prediction and optimization) • Strong leadership and capacity to work as a ...

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 ...

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 ...

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 ...

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How much do xgboost jobs pay per hour?

As of Jul 30, 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.

Is XGBoost still popular?

XGBoost remains a popular machine learning algorithm used in data science and AI roles due to its high performance and efficiency in structured data tasks. It is widely valued for its speed, scalability, and effectiveness in competitions like Kaggle, making it a common skill for data analysts and machine learning engineers.

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.

Is 40 too late for data science?

Age is generally not a barrier to entering data science roles, including positions involving XGBoost and other machine learning tools. Many professionals successfully transition into data science later in their careers by acquiring relevant skills, certifications, and experience. Employers value skills and problem-solving ability over age, making it possible to start or switch into data science at 40 or older.

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.

Is data science still worth it in 2026?

Data science remains a valuable field in 2026, with roles involving machine learning models like XGBoost, data analysis, and predictive modeling. Skills in programming, statistics, and tools such as Python and SQL are essential for success in this evolving industry.

Is ML a high paying job?

Machine learning roles, including positions involving XGBoost, are generally well-paid due to high demand for data science and AI skills. Salaries vary based on experience, location, and industry, but professionals with expertise in machine learning tools and algorithms often earn above average wages in the tech sector.
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Xgboost jobs near you
Infographic showing various Xgboost job openings in the United States as of July 2026, with employment types broken down into 97% Full Time, and 3% Contract. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $75,411 per year, or $36.3 per hour.

Senior Machine Learning Engineer

The Brixton Group

Jersey City, NJ • On-site

$114K - $157K/yr

Full-time

Re-posted 5 days ago

Job description

Job Summary:
The Brixton Group is a financial services company seeking a Senior Machine Learning Engineer. This role involves designing and operationalizing a multi-tier classification engine for incident classification, utilizing advanced machine learning techniques.
Responsibilities:
• Design the three-tier classification engine using rules-based logic, XGBoost, and LLM agent orchestration.
• Build feature engineering pipelines for temporal, topological, and semantic scoring models.
• Train and validate XGBoost models using historical ServiceNow incident datasets.
• Implement SHAP for classification transparency and audit readiness.
• Develop automated monthly retraining pipelines using AWS Lambda and MLflow.
• Implement model drift detection frameworks using Evidently.
Qualifications:
Required:
• Python
• XGBoost
• MLflow
• Kafka Streaming
• SQL
Company:
The Brixton Group is a technology staffing and project solutions company. Founded in 1998, the company is headquartered in Charlotte, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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