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Ml Inference Jobs in Raleigh, NC (NOW HIRING)

Berriehill Research

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 ...

Qualcomm

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 ...

CYNET SYSTEMS

Data Scientist

Cary, NC · On-site

$65 - $70/hr

Proven experience designing, deploying, and operating production ML and/or GenAI solutions, including APIs, batch, and real-time inference. * Experience in developing Machine Learning models using ...

Spgi

Vice President, Data Science

Raleigh, NC

$177K - $350K/yr

Strong understanding of production ML system design, including batch vs real-time inference, model serving patterns, performance trade-offs, and failure modes. * Experience operating models in ...

S&P Global

Vice President, Data Science

Raleigh, NC · On-site

$177K - $350K/yr

Strong understanding of production ML system design, including batch vs real-time inference, model serving patterns, performance trade-offs, and failure modes. * Experience operating models in ...

ARA

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 ...

Lindsay & Brownell

AI Engineer

Raleigh, NC · On-site

... inference infrastructure and pipelines. * Implement MLOps pipelines for continuous integration, deployment, and lifecycle management using Azure ML and GitHub Actions. * Ensure compliant change ...

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All JobsMl Inference JobsMl Inference Jobs in Raleigh, NC

Ml Inference information

See Raleigh, NC salary details

$36.5K

$119.3K

$191K

How much do ml inference jobs pay per year?

As of Aug 7, 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.

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?

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.

Is ML inference a high paying job?

ML inference roles are generally well-paying, especially for those with skills in machine learning frameworks, programming, and cloud platforms. Salaries vary based on experience, location, and industry, but they tend to be higher than average for tech-related positions.
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What cities near Raleigh, NC are hiring for Ml Inference jobs? Cities near Raleigh, NC with the most Ml Inference job openings:
Ml Inference jobs near you
Infographic showing various Ml Inference job openings in Raleigh, NC as of August 2026, with employment types broken down into 92% Full Time, 3% Part Time, and 5% Contract. Highlights an 82% Physical, 4% Hybrid, and 14% Remote job distribution, with an average salary of $119,312 per year, or $57.4 per hour.

Senior MLOps Engineer- Remote[Candidates must work PST hours]

OMG Technology

Raleigh, NC • Remote

Contractor

This job post has expired today. Applications are no longer accepted.

Job description

Salary:

This opportunity is for aSenior MLOps Engineerrole with one of our clients. Please find the job description below.


Position Overview :

Role: Sr MLOps Engineer
Location:Remote[Candidates must work PST hours]
Duration:12+Months
ContractRole
Rate: $60/hr on W2 | $70/hr on C2C


Job Summary

The Sr. Engineer, Machine Learning Operations, with minimal guidance, works independently and with crossfunctional partnersincluding biostatisticians, bioinformatics scientists, AI scientists, and software engineersto deploy, operate, and scale machine learning solutions in production for advanced cancer screening and precision oncology applications.The role designs, builds, and maintains robust ML platforms and pipelines that ensure reliability, security, and compliance across the full model lifecyclefrom data ingestion, model training, versioning and evaluation, through deployment, monitoring, and continuous improvement. This role serves as a key resource, applying indepth practical knowledge of ML Operations, software engineering, and cloud infrastructure to solve complex problems across multiple projects, ensuring AI/ML models are production-ready, observable,and aligned with the company's mission to help eradicate cancer.

Essential Duties

Include, but are not limited to, the following:

  • Designs, implements, and maintains endtoend MLOps pipelines for training, validation, deployment, and monitoring of ML and AI models used in cancer screening and precision oncology solutions.
  • Builds and operates scalable, secure ML infrastructure on cloud and container platforms (e.g., AWS/Azure/GCP, Docker, Kubernetes) to support batch and realtime inference workloads.
  • Implements CI/CD workflows for ML (data, model, and code), including automated testing, packaging, and promotion of models across development, staging, and production environments.
  • Establishes and manages model and data versioning, experiment tracking, and lineage to ensure reproducibility, auditability, and effective model governance.
  • Develops and maintains monitoring, logging, and alerting for model performance, data quality, drift, and system health, defining and meeting SLOs/SLAs for critical ML services.
  • Collaborates with data scientists, bioinformatics and biostatistics partners, and software/platform engineering teams to translate experimental workflows into productiongrade services integrated into customerfacing and internal applications.
  • Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork.
  • Support and comply with the companys Quality Management System policies and procedures.
  • Maintain regular and reliable attendance.
  • Ability to act with an inclusion mindset and model these behaviors for the organization.
  • Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 90% of a typical working day.
  • Ability to travel 5% of working time away from work location, may include overnight/weekend travel.

Minimum Qualifications

  • Bachelors Degree in a field related to essential duties; or Associates Degree and 2 years of relevant experience.; or High School Diploma or General Education Degree (GED) and 4 years of relevant experience.
  • 5 years of relevant job-related experience.
  • Demonstrated experience with Python, at least one major ML framework (e.g., TensorFlow, PyTorch, scikitlearn), containerization and orchestration technologies (e.g., Docker, Kubernetes), and a major cloud platform (e.g., AWS, Azure, GCP) supporting ML workloads.
  • Demonstrated ability to perform the essential duties of the position with or without accommodation.
  • Applicants must be currently authorized to work in country where work will be performed on a full or part-time basis. We are unable to sponsor or take over sponsorship of employment visas at this time.

Preferred Qualifications

  • 2+ years of life sciences industry experience working with biological data.
  • 2+ years of industry experience in molecular diagnostics, preferably cancer diagnostics.
  • Expertise in data mining approaches within healthcare settings generating insight from routinely collected healthcare data.
  • Scientific understanding of cancer biology
  • Strong programming ability in Python and experience with at least one major ML framework (e.g., TensorFlow, PyTorch, scikit-learn).
  • Hands-on experience deploying and operating machine learning models in production, including experience with CI/CD pipelines, model packaging, and automated deployment.

Other Job Details

  • Number of Openings:23
  • Work Schedule:Must be available to work PST hours
  • Industry Experience:Not required; strong technical expertise is the primary focus
  • Interviews:Video interviews.
  • Docs required:ID proof will be required