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Machine Learning Engineer Opt Jobs in Raleigh, NC

ExtendMyTeam

Machine Learning Engineer

Cary, NC

Position Summary We are seeking a Machine Learning Engineer to help design, deploy, and support production machine learning systems within a collaborative engineering organization. This individual ...

CoVar

Machine Learning Engineer

Durham, NC

Machine Learning Engineer About CoVar CoVar is a small AI/ML R&D software company in Durham, NC, that uses artificial intelligence to solve problems that matter. We develop AI/ML tools to help the ...

Vadum, Inc.

Machine Learning Engineer

Raleigh, NC · On-site

$96K - $137K/yr

We are seeking a talented and innovative Machine Learning Engineer to join our dynamic team. In this role, you will be responsible for designing and developing machine learning prototypes, as well as ...

Vadum Inc

Machine Learning Engineer

Raleigh, NC · On-site

We are seeking a talented and innovative Machine Learning Engineer to join our dynamic team. In this role, you will be responsible for designing and developing machine learning prototypes, as well as ...

Vadum Inc

Machine Learning Engineer

Raleigh, NC

We are seeking a talented and innovative Machine Learning Engineer to join our dynamic team. In this role, you will be responsible for designing and developing machine learning prototypes, as well as ...

Q2 Software, Inc.

Machine Learning Engineer

Cary, NC · On-site

As a Machine Learning Engineer, you will help build and operate production systems that power our fraud products. You'll work closely with data scientists and engineers to bring models into ...

Q2

Machine Learning Engineer

Cary, NC · On-site

As a Machine Learning Engineer, you will help build and operate production systems that power our fraud products. You'll work closely with data scientists and engineers to bring models into ...

LexisNexis

Machine Learning Engineer Lead

Raleigh, NC · On-site

$115.40K - $192.30K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This ...

RELX Group plc

Machine Learning Engineer Lead

Raleigh, NC · On-site

$115.40K - $192.30K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This ...

LexisNexis

Machine Learning Engineer Lead

Raleigh, NC

$115.40K - $192.30K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This ...

RELX

Machine Learning Engineer Lead

Raleigh, NC

$115.40K - $192.30K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This ...

OptiTrack

Machine Learning & Operations Engineer

Durham, NC · Remote

$71.10K - $96.20K/yr

About the Role OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale an MLOps system and provide other support to teams working on projects involving machine learning.

OptiTrack

Machine Learning & Operations Engineer

Durham, NC · Remote

$67.20K - $90.80K/yr

About the Role OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale an MLOps system and provide other support to teams working on projects involving machine learning.

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All JobsMachine Learning Engineer Opt JobsMachine Learning Engineer Opt Jobs in Raleigh, NC

Machine Learning Engineer Opt information

See Raleigh, NC salary details

$30.6K

$125.2K

$188.1K

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

As of May 29, 2026, the average yearly pay for machine learning engineer opt in Raleigh, NC is $125,174.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,700.00 and $150,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

What are popular job titles related to Machine Learning Engineer Opt jobs in Raleigh, NC? For Machine Learning Engineer Opt jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Opt jobs in Raleigh, NC look for? The top searched job categories for Machine Learning Engineer Opt jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Machine Learning Engineer Opt jobs? Cities near Raleigh, NC with the most Machine Learning Engineer Opt job openings:
Machine Learning Engineer Opt jobs near you

Machine Learning Engineer

ExtendMyTeam

Cary, NC

Full-time

Posted 10 days ago

Job description

Join a high-growth financial technology organization focused on building modern digital banking, payments, lending, and risk solutions for financial institutions and fintech partners. This team is investing in machine learning and analytics capabilities to help improve fraud detection, predictive insights, and operational decision-making across customer-facing products.

This is an opportunity to work on applied machine learning systems that directly support real-world fraud and risk workflows. The team owns solutions end-to-end and is focused on building scalable, production-ready ML applications that deliver measurable customer impact.

Position Summary

We are seeking a Machine Learning Engineer to help design, deploy, and support production machine learning systems within a collaborative engineering organization. This individual will work closely with software engineers, data scientists, and product teams to operationalize machine learning models, improve ML infrastructure, and support scalable analytics workflows.

This is a hands-on engineering role focused on production systems, model deployment, APIs, pipelines, and ML operations rather than purely research-oriented machine learning work.

Responsibilities

  • Build and maintain systems and pipelines supporting machine learning training, evaluation, inference, and monitoring

  • Deploy and support machine learning models in production environments

  • Write clean, scalable, maintainable, and well-tested Python code

  • Support monitoring, troubleshooting, and optimization of production ML systems and data pipelines

  • Collaborate cross-functionally with engineering, data science, and product teams to operationalize ML solutions

  • Improve the reliability, scalability, and performance of ML infrastructure and services

  • Contribute to tooling and processes that support the machine learning development lifecycle

  • Participate in code reviews, technical discussions, and collaborative problem solving

Required Qualifications

  • 2+ years of experience in machine learning engineering, software engineering, or related technical experience

  • Strong Python development experience

  • Experience working with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn

  • Experience deploying or supporting machine learning models in production environments

  • Experience writing clean, maintainable code and using version control tools such as Git

  • Exposure to cloud platforms such as AWS, GCP, or Azure

  • Understanding of taking machine learning models from research/development into production systems

Additional Information

  • Hybrid work environment based in Cary, NC

  • Applicants must be authorized to work in the U.S. without sponsorship

  • Competitive compensation, benefits, flexible time off, and career development opportunities