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Ml Inference Jobs in Canton, GA (NOW HIRING)

Cisco

Applied AI Scientist

Atlanta, GA · On-site

Explore and evaluate new AI/ML techniques, tools, and methodologies, applying relevant innovations ... and inference efficiency to minimize cost and latency while preserving accuracy. * MLOps ...

Honeywell

Sr Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

... ML workloads * Build and maintain data pipelines for AI product lifecycle, including training data preparation, feature engineering, and inference data flows * Develop and optimize RAG (Retrieval ...

Honeywell

Sr Data Engineer

Atlanta, GA

$110K - $132K/yr

... ML workloads * Build and maintain data pipelines for AI product lifecycle, including training data preparation, feature engineering, and inference data flows * Develop and optimize RAG (Retrieval ...

Warnerbros

Staff Software Engineer

Atlanta, GA · On-site

The features this framework produces - ML- and LLM-generated alike - power everything from analytics to training to inference to user-facing rendering. What You'll Do * Design and own infrastructure ...

Five and Fly

Machine Learning Engineer

Atlanta, GA · On-site

... ML systems. * Proficiency in Python and libraries such as PyTorch, TensorFlow, Scikit-Learn, Hugging Face Transformers. * Hands-on experience with LLMs/SLMs (fine-tuning, prompt design, inference ...

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All JobsMl Inference JobsMl Inference Jobs in Canton, GA

Ml Inference information

See Canton, GA salary details

$35.4K

$115.9K

$185.5K

How much do ml inference jobs pay per year?

As of Sep 3, 2026, the average yearly pay for ml inference in Canton, GA is $115,888.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,000.00 and $128,400.00 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 cities near Canton, GA are hiring for Ml Inference jobs?

Cities near Canton, GA with the most Ml Inference job openings:

Ml Inference jobs near you

Python MLOps Specialist (SageMaker, MLflow) - Q125

R2 Technologies Corporation

Alpharetta, GA • On-site

$49 - $67.50/hr

Full-time

Medical, Retirement, PTO

Re-posted yesterday

Job description

Overview:
R2 Technologies Corporation (R2), headquartered in Alpharetta, GA, is a leading IT services provider specializing in Java, .NET, Big Data, Cloud Computing (AWS, GCP, Azure), Artificial Intelligence (AI), Machine Learning (ML), software development, project management, SAP, and enterprise resource planning (ERP). We empower clients-from startups to Fortune 1000 companies-with scalable, platform-based solutions and data-driven insights using modern cloud technologies. Our commitment to blending highly skilled talent with innovative productivity platforms ensures rapid delivery of business value, making us one of the most respected and trusted technology companies in the United States. At R2, we're passionate about driving operational excellence and competitive advantage for our clients through cutting-edge AI, ML, and cloud solutions. Join our team and help shape the future of technology innovation!
Python MLOps Specialist (SageMaker, MLflow)
Location: Alpharetta, GA (willing to travel to client locations)
Employment Type: Full-Time (W2)
Role Overview
We are seeking a skilled Python MLOps Specialist to streamline machine learning operations using Python with AWS SageMaker or MLflow. This role focuses on automating model deployment and management through CI/CD and DevOps practices.
Key Responsibilities
  • Develop Python-based MLOps workflows to automate ML model training and deployment.
  • Implement CI/CD pipelines for ML models using SageMaker, MLflow, or Kubeflow.
  • Manage model lifecycle processes, including versioning, testing, and monitoring with MLflow.
  • Leverage AWS SageMaker for scalable model training and inference in production.
  • Collaborate with DevOps teams to integrate MLOps into broader CI/CD ecosystems.
  • Ensure model governance, security, and performance in automated ML operations.

Required Qualifications
  • Bachelor's degree in Computer Science, Software Engineering, or a related field (or equivalent experience).
  • 3 years of experience in Python development with a focus on MLOps and DevOps practices.
  • Proficiency in using SageMaker or MLflow for automating machine learning workflows.
  • Experience with CI/CD pipelines for deploying and managing ML models in production.
  • Strong understanding of MLOps principles and their integration with Python-based systems.

Preferred Qualifications
  • Familiarity with Kubeflow for orchestrating MLOps workflows on Kubernetes.
  • Exposure to cloud platforms like AWS or GCP for scalable MLOps deployments.
  • Knowledge of monitoring tools like Prometheus for ML model observability.

Compensation & Benefits
  • Competitive salary and comprehensive benefits package (healthcare, PTO, 401k).
  • Opportunities for professional growth and upskilling in AI and cloud technologies.

R2 Technologies Corporation is an equal opportunity employer and values diversity in the workplace.
Skills:
Python, MLOps, SageMaker, MLflow, Kubeflow, CI/CD, DevOps

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