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Ml Inference Jobs in Raleigh, NC (NOW HIRING)

Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) * RAG ... ML infrastructure, or data platforms (principal scope: portfolio strategy, multi-team alignment ...

Senior AI Systems Engineer

Raleigh, NC · On-site +1

$92K - $126K/yr

Experience with AI/ML frameworks and tooling such as PyTorch, Hugging Face, or similar ecosystems ... Experience with model serving, inference optimization, or AI platform tools such as MLflow ...

Senior AI Performance Architect

Raleigh, NC · On-site

$162K/yr

AI inference and training systems must scale to a large number of accelerators, servers and racks ... Understand trends in ML network design through customer engagements and latest academic research ...

Machine Learning & Operations Engineer

Durham, NC · Remote

$67K - $90K/yr

Design and maintain automated ML training pipelines. * Build infrastructure for large-scale ... Experience with model optimization, inference acceleration, or edge deployment * Experience ...

Machine Learning & Operations Engineer

Durham, NC · Remote

$67K - $90K/yr

Design and maintain automated ML training pipelines. * Build infrastructure for large-scale ... Experience with model optimization, inference acceleration, or edge deployment * Experience ...

Machine Learning & Operations Engineer

Durham, NC · Remote

$71K - $96K/yr

Design and maintain automated ML training pipelines. * Build infrastructure for large-scale ... Experience with model optimization, inference acceleration, or edge deployment * Experience ...

Senior AI Systems Engineer

Raleigh, NC · On-site

$92K - $126K/yr

Experience with AI/ML frameworks and tooling such as PyTorch, Hugging Face, or similar ecosystems ... Experience with model serving, inference optimization, or AI platform tools such as MLflow ...

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Ml Inference information

See Raleigh, NC salary details

$36.5K

$119.3K

$191K

How much do ml inference jobs pay per year?

As of Jun 24, 2026, the average yearly pay for ml inference in Raleigh, NC is $119,312.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,800.00 and $132,200.00 per year, depending on experience, location, and employer.

What is ML inference?

ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.

What is the difference between Ml Inference vs Data Scientist?

AspectML InferenceData Scientist
Required CredentialsKnowledge of machine learning models, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentDeploying models in production, real-time data processingData analysis, model development, research
Industry UsageAI product deployment, software companiesResearch institutions, tech firms, consulting

ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.

Which 3 jobs will survive AI?

For ML Inference roles, jobs that require complex problem-solving, creativity, and emotional intelligence are more likely to persist, such as data scientists, AI ethics specialists, and machine learning engineers. These roles involve tasks that are difficult to automate and often require specialized skills, domain knowledge, and critical thinking. Continuous learning and expertise in AI tools and programming languages like Python or TensorFlow can also enhance job security in this field.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, specialized skills in deep learning, and strong industry demand can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Achieving this level typically requires advanced degrees, certifications, and a proven track record of impactful projects.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch. These positions usually involve leadership responsibilities, strategic planning, and may require multiple years of specialized experience or advanced degrees.

Is ML a high paying job?

Machine Learning (ML) inference roles are generally well-paid due to the specialized skills required, such as knowledge of algorithms, programming, and data analysis. Salaries vary based on experience, location, and industry, but they tend to be higher than average for tech positions. Advanced roles often require proficiency with tools like TensorFlow or PyTorch and may include certifications or advanced degrees.

What are some common challenges faced by ML Inference Engineers when deploying models to production?

ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.

What are the key skills and qualifications needed to thrive in ML Inference, and why are they important?

To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.
What are popular job titles related to Ml Inference jobs in Raleigh, NC? For Ml Inference jobs in Raleigh, NC, the most frequently searched job titles are:
What cities near Raleigh, NC are hiring for Ml Inference jobs? Cities near Raleigh, NC with the most Ml Inference job openings:
Infographic showing various Ml Inference job openings in Raleigh, NC as of June 2026, with employment types broken down into 60% Full Time, 20% Part Time, and 20% Contract. Highlights an 60% In-person, and 40% Remote job distribution, with an average salary of $119,312 per year, or $57.4 per hour.
Senior AI Platform Engineer (Data and Analytics Cloud Engineer)

Senior AI Platform Engineer (Data and Analytics Cloud Engineer)

Truist

Raleigh, NC • On-site

$101K - $139K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 days ago


Truist rating

8.2

Company rating: 8.2 out of 10

Based on 110 frontline employees who took The Breakroom Quiz

37th of 141 rated banks


Job description

The position is described below. If you want to apply, click the Apply Now button at the top or bottom of this page. After you click Apply Now and complete your application, you'll be invited to create a profile, which will let you see your application status and any communications. If you already have a profile with us, you can log in to check status.

Need Help?

If you have a disability and need assistance with the application, you can request a reasonable accommodation. Send an email to Accessibility (accommodation requests only; other inquiries won't receive a response).

Regular or Temporary:

Regular

Language Fluency: English (Required)

Work Shift:

1st shift (United States of America)Please review the following job description:Senior Engineer/Platform Leader accountable for designing, building, and operating secure, scalable AI/ML and Generative AI (GenAI) platforms in the cloud. This role develops and maintains reusable platform capabilities (e.g., model and prompt development environments, feature/model/prompt management, retrieval and knowledge-grounding patterns, data access patterns, CI/CD automation, evaluation/testing, and observability) so teams can deliver business outcomes faster while meeting Truist technology standards, security requirements, and regulatory obligations.

ESSENTIAL DUTIES AND RESPONSIBILITIES
Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time.

  • Design, build, and execute the AI/ML and GenAI platform strategy aligned to enterprise architecture, security, and risk standards.

  • Own the engineering and lifecycle management of AI/ML platform components (e.g., development workspaces, training/inference patterns, model registry, feature storage patterns, experiment tracking, prompt/version management, retrieval-augmented generation (RAG) enablement, and reusable templates) for safe and deliberate consumption across the organization.

  • Establish and champion DevSecOps practices for platform delivery, including GitLab source control, build automation, and CI/CD pipelines for infrastructure and application deployments.

  • Deploy infrastructure as code (IaC) to the cloud using Terraform modules and pipelines; define standards for environments, networking, identity, secrets, encryption, logging, and configuration management.

  • Partner with Cybersecurity, Risk, and other 2nd line of defense teams to implement and evidence required security controls (e.g., IAM least privilege, network segmentation, encryption, vulnerability management, audit logging, and policy-as-code) across platform services.

  • Implement governance patterns for AI/ML and GenAI (e.g., model and prompt lifecycle controls, lineage/traceability for data, prompts, and outputs, approvals, change management, risk assessments, and operational readiness) consistent with enterprise data governance and regulatory obligations.

  • Provide technical leadership and hands-on engineering to solve complex platform problems (performance, reliability, scalability, cost, and security), and guide engineers through designs, reviews, and delivery.

  • Build platform reliability through automation and observability (monitoring, logging, tracing, SLOs), and partner with production support teams to increase resiliency, reduce toil, and improve time to recover.

  • Enable self-service platform consumption via standardized APIs, reusable pipelines, templates, and documentation; in an Agile environment, may serve as an Agile/DevSecOps champion to accelerate delivery while maintaining compliance.

QUALIFICATIONS
Required Qualifications:
The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
1. Undergraduate degree in either computer science, analytics, data engineering, finance or equivalent degree.
2. At least 3 years of experience driving enterprise data strategy, data execution, data engineering or software delivery
3. Expert problem solving skills and being able to define detailed strategies
4. Experience in financial services or payments industry
5. Experience in meeting regulatory obligations and operating in a highly regulatory environment on the cloud
6. Experience in building a high performing team

Preferred Qualifications:

  • Master's degree and/or 8+ years of progressive experience delivering complex cloud platforms, preferably supporting AI/ML or analytics workloads at enterprise scale.

  • Experience building AI/ML platforms and/or MLOps capabilities (e.g., training/inference automation, model packaging and deployment, model registry, experiment tracking, and operational monitoring).

  • Experience with container platforms and orchestration (e.g., Kubernetes/EKS), API enablement, and modern ML tooling (e.g., Python ML ecosystem) to operationalize models and GenAI services.

  • Deep expertise in AWS (compute, networking, security/IAM, logging/monitoring, and managed services) and moderate experience with Azure services and deployment patterns.

  • Hands-on DevOps/DevSecOps experience building CI/CD pipelines (GitLab), including automated testing, security scanning, artifact management, and controlled deployments across environments.

  • Strong infrastructure-as-code experience deploying cloud components using Terraform; ability to build reusable modules and enforce standards/guardrails.

  • Relevant cloud and security certifications (preferred), such as AWS Solutions Architect/DevOps Engineer, AWS Security Specialty, Azure Administrator/Architect, and/or Terraform certification; strong mentoring/coaching skills for engineers distributed across onshore and offshore teams.

The annual base salary for this position is $130000 - $170000.

General Description of Available Benefits for Eligible Employees of Truist Financial Corporation: All regular teammates (not temporary or contingent workers) working 20 hours or more per week are eligible for benefits, though eligibility for specific benefits may be determined by the division of Truist offering the position.Truist offers medical, dental, vision, life insurance, disability, accidental death and dismemberment, tax-preferred savings accounts, and a 401k plan to teammates. Teammates also receive no less than 10 days of vacation (prorated based on date of hire and by full-time or part-time status) during their first year of employment, along with 10 sick days (also prorated), and paid holidays. For more details on Truist's generous benefit plans, please visit our Benefits site. Depending on the position and division, this job may also be eligible for Truist's defined benefit pension plan, restricted stock units, and/or a deferred compensation plan. As you advance through the hiring process, you will also learn more about the specific benefits available for any non-temporary position for which you apply, based on full-time or part-time status, position, and division of work.

Truist is an Equal Opportunity Employer that does not discriminate on the basis of race, gender, color, religion, citizenship or national origin, age, sexual orientation, gender identity, disability, veteran status, or other classification protected by law. Truist is a Drug Free Workplace.

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About Truist

Sourced by ZipRecruiter

Truist is combining distinctive personal service with investments in innovation to create transformational client experiences. We believe the unique blend of human touch and innovative technology will set us apart, instill confidence, and build deeper levels of trust with our clients

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

Charlotte, NC, US

Year founded

2019