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Ml Inference Jobs in Raleigh, NC (NOW HIRING)

Compunnel

Machine Learning Engineer Lead

Raleigh, NC · On-site

$99K - $131K/yr

... inference systems using containerization and Kubernetes. • Drive the deployment and optimization of LLM, Generative AI, and RAG solutions in production environments. • Design cloud-based AI/ML ...

Apple

ML Engineer - Creator Studio

Cary, NC

$142K - $263K/yr

We're looking for ML engineers who want to define the product. That means less time on models in ... on-device inference. Investigate model and agent failures end to end - from the user-visible ...

Apple

ML Engineer - Creator Studio

Cary, NC

$142K - $263K/yr

We're looking for ML engineers who want to define the product. That means less time on models in ... on-device inference. Investigate model and agent failures end to end - from the user-visible ...

Apple

ML Engineer - Creator Studio

Cary, NC

$142K - $263K/yr

We're looking for ML engineers who want to define the product. That means less time on models in ... on-device inference. Investigate model and agent failures end to end - from the user-visible ...

Apple

ML Engineer - Creator Studio

Cary, NC

$142K - $263K/yr

We're looking for ML engineers who want to define the product. That means less time on models in ... on-device inference. Investigate model and agent failures end to end - from the user-visible ...

Apple

ML Engineer - Creator Studio

Cary, NC

$142K - $263K/yr

We're looking for ML engineers who want to define the product. That means less time on models in ... on-device inference. Investigate model and agent failures end to end - from the user-visible ...

Northern Base

AI Solution Lead

Cary, NC · On-site

... AI/ML models for real-time and batch inference ✔ Hands-on experience with Kubernetes, Helm, containerization, and cloud-native deployments ✔ Experience building event-driven, resilient ...

Deloitte

AI Engineer Consultant

Raleigh, NC · Hybrid

Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills). A successful candidate would possess ...

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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 26, 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 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.

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 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 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 job categories do people searching Ml Inference jobs in Raleigh, NC look for?

The top searched job categories for Ml Inference jobs in Raleigh, NC are:

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 1% Internship, 92% Full Time, 4% Part Time, and 3% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $119,312 per year, or $57.4 per hour.

Need AI/ML Data Science Lead contract jobs at Cary, NC

Cary, NC • On-site

Tech Mirrors
See more jobs at Tech Mirrorsexternal

$120 - $180/hr

Other

Posted 8 days ago

Job description

Job Title: AI/ML Data Science Lead

Location: Cary, NC (Need locals)

Duration: Contract

Key Responsibilities
  • Team Leadership: Lead the solution and a team of data scientists delivering AI and ML solution for marketing and business engagement use cases
  • Ownership: Accountability for technical decisions, project outcomes, timelines, and production stability within a defined domain.
  • Planning and Business alignment: Lead the planning and execution of data science use cases, ensuring alignment with business goals and objectives.
  • Model Development: Design, train, and optimize machine learning and deep learning models for a variety of marketing and business engagement use cases
  • Data Analysis: Analyze complex data sets to identify trends, patterns, and actionable insights that can inform business strategies.
  • Collaboration: Collaborate with stakeholders and cross-functional teams to develop and implement data-driven solutions.
  • Platform Integration: Enable seamless integration of AI capabilities into business applications and workflows through APIs, SDKs, and microservices.
  • Stakeholder Communication: Visualize data, create reports, and present findings to senior management and cross-functional teams.
  • Develop statistical models, analytics, and Machine Learning algorithms using Python and cloud tools (Azure).
  • Research and Innovation: Stay up to date with the latest advances in AI, Data Science, and Machine Learning.
  • ML-Ops Best Practices: Optimize platform components for efficiency, scalability, and reliability using best practices in distributed computing, resource management, and cloud-native architectures.
Essential Business Experience and Technical Skills Required
  • Bachelor’s or master’s degree in computer science, Data Science, Engineering, Mathematics, or a related field.
  • 8+ years of overall experience in AI/ML engineering and/or data science.
  • 5+ years of insurance business and/or financial industry experience with sales, marketing, and/or customer engagement analytics.
  • 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 Python (preferably in the cloud)
  • Familiarity with best practices for responsible AI, including data privacy, bias mitigation, and/or model monitoring.
  • Strong SQL knowledge and data analysis skills for data anomaly detection and Exploratory Data Analysis.
  • Experience with Dominos, Power BI, and/or Azure ML
  • Statistical Knowledge: A strong understanding of statistics and mathematics is essential for data analysis and prediction.
  • Use predictive modeling or AI solutions to increase and optimize customer experience/communication, revenue generation, ad targeting, and other business outcomes
  • Very good presentation skills to present results clearly and effectively by creating presentations with storytelling, visualizations & results
  • Very good problem solver and excellent communication skills – both written and verbal
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