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Machine Learning Engineer Hybrid Jobs (NOW HIRING)

X4 Engineering

Machine Learning Engineer

Austin, TX · On-site

$140K - $180K/yr

🚀 Machine Learning Engineer 📍 Austin, TX (Hybrid/Remote Considered) 💰 $140,000 - $180,000 Base We're partnering with a fast-growing energy firm looking to hire a Machine Learning Engineer to ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

Intraedge

Machine Learning Engineer

Sunrise, FL · On-site

Machine Learning Engineer - Generative Al Long term contract Sunrise, FL (Hybrid-3 days onsite) Direct client- Immediate client interview We are seeking a Machine Learning Engineer to design, build ...

ExtendMyTeam

Machine Learning Engineer

Austin, TX

Position Summary We are seeking a Machine Learning Engineer to help design, implement, and scale AI ... Hybrid opportunity located in Austin, TX * Applicants must be authorized to work in the U.S ...

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All JobsMachine Learning Engineer Hybrid Jobs

Machine Learning Engineer Hybrid information

See salary details

$31.5K

$128.8K

$193.5K

How much do machine learning engineer hybrid jobs pay per year?

As of Jul 8, 2026, the average yearly pay for machine learning engineer hybrid in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Engineer Hybrid vs Data Scientist?

AspectMachine Learning Engineer HybridData Scientist
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops, tests, deploys ML models; collaborates with engineering teamsAnalyzes data, builds models, interprets results; works across departments
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

Machine Learning Engineer Hybrid focuses on developing and deploying ML models within engineering environments, often requiring coding and deployment skills. Data Scientists analyze data, build models, and interpret results, often in research or strategic roles. While both roles require strong analytical skills and knowledge of ML, the Engineer Hybrid emphasizes deployment and integration, whereas Data Scientists focus on data analysis and insights.

More about Machine Learning Engineer Hybrid jobs
What cities are hiring for Machine Learning Engineer Hybrid jobs? Cities with the most Machine Learning Engineer Hybrid job openings:
What states have the most Machine Learning Engineer Hybrid jobs? States with the most job openings for Machine Learning Engineer Hybrid jobs include:
What job categories do people searching Machine Learning Engineer Hybrid jobs look for? The top searched job categories for Machine Learning Engineer Hybrid jobs are:
Machine Learning Engineer Hybrid jobs near you
Infographic showing various Machine Learning Engineer Hybrid job openings in the United States as of July 2026, with employment types broken down into 95% Full Time, 2% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer

X4 Engineering

Austin, TX • On-site

$140K - $180K/yr

Other

Posted 14 days ago

Job description

🚀 Machine Learning Engineer

📍 Austin, TX (Hybrid/Remote Considered)

💰 $140,000 - $180,000 Base


We're partnering with a fast-growing energy firm looking to hire a Machine Learning Engineer to join a highly technical platform engineering team supporting traders, analysts, and quantitative researchers.


This is not a pure data science role. We're looking for an engineer who enjoys building robust production systems, scaling data and ML infrastructure, and working closely with front-office stakeholders to deliver real business impact.


What you'll be doing:

  • Building and maintaining ML and data platforms used for forecasting, optimization, and trading workflows
  • Designing scalable cloud-native infrastructure and deployment pipelines
  • Productionizing quantitative models and analytics tools
  • Developing distributed data and compute systems
  • Working directly with traders and business users to deliver reliable solutions
  • Driving engineering best practices across CI/CD, observability, testing, and automation


Tech stack includes:

Python | AWS | Kubernetes | Docker | Terraform | Airflow | Spark | MLflow | Databricks | Kafka | CI/CD

We're interested in people from backgrounds such as:

✔ Machine Learning Engineering

✔ MLOps Engineering

✔ Platform Engineering

✔ Software Engineering (with ML/Data exposure)

✔ Quant Development

✔ Infrastructure Engineering


Ideal candidates will have strong Python skills, cloud and DevOps experience, and a track record of building production systems. Experience within energy, trading, forecasting, or quantitative environments is beneficial but not essential.


If you'd like to learn more, please send me a message or apply directly.


They prefer the role to be worked on a hybrid model of 1-2 days a week. Salary offered is $140,000-$180,000.

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