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Software Engineer Ai Model Training Jobs in Callahan, FL

Smart AutoCare

Senior Software Engineer

Jacksonville, FL · On-site

$113K - $149K/yr

Job Title: Sr Software Engineer Department: IT Pay Grade: Overtime Eligibility: Exempt Date: June ... AI Integration: Actively leverage and champion the use of AI-assisted engineering tools (e.g ...

Smart AutoCare

Senior Software Engineer

Jacksonville, FL

$113K - $149K/yr

Job Title: Sr Software Engineer Department: IT Pay Grade: Overtime Eligibility: Exempt Date: June ... AI Integration: Actively leverage and champion the use of AI-assisted engineering tools (e.g ...

Deloitte

Agentic Software Engineer III

Jacksonville, FL · On-site

$53.25 - $71.50/hr

Work you'll do As a Software Engineer III on the Customer team, you will support AI-assisted ... and training; licensure and certifications; and other business and organizational needs. The ...

Deloitte

Agentic Software Engineer II

Jacksonville, FL

$90K - $123K/yr

Work you'll do As a Software Engineer II on the Customer team, you will support AI-assisted ... and training; licensure and certifications; and other business and organizational needs. At ...

Deloitte

AI Engineer Consultant

Jacksonville, FL · Hybrid

We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that ... model training, real-time inference, and LLM applications using Claude-, GPT/Codex-, and Gemini ...

Catalyst Labs

ML Engineer

Jacksonville, FL · On-site

... AI lifecycle, including data acquisition, preprocessing, model training, deployment, inference, and monitoring in production environments. • Participate in continuous improvement of the ML ...

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All JobsSoftware Engineer Ai Model Training JobsSoftware Engineer Ai Model Training Jobs in Callahan, FL

Software Engineer Ai Model Training information

See Callahan, FL salary details

$56.3K

$130.9K

$182.3K

How much do software engineer ai model training jobs pay per year?

As of Aug 21, 2026, the average yearly pay for software engineer ai model training in Callahan, FL is $130,868.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,500.00 and $153,500.00 per year, depending on experience, location, and employer.

What does a software engineer AI model training do?

A Software Engineer specializing in AI Model Training is responsible for designing, developing, and optimizing machine learning models. Their work involves preparing and processing large datasets, selecting appropriate algorithms, implementing training pipelines, and evaluating model performance. They collaborate closely with data scientists and other engineers to ensure that AI models are accurate, efficient, and suitable for deployment in real-world applications. Additionally, they may help maintain infrastructure for model training and contribute to research and development of new AI techniques.

What are the key skills and qualifications needed to thrive as a software engineer AI model training?

To excel as a Software Engineer in AI Model Training, you need strong programming skills (especially in Python), a solid grasp of machine learning fundamentals, and typically a degree in computer science or a related field. Experience with frameworks like TensorFlow or PyTorch, familiarity with data processing tools, and sometimes certifications in AI or ML are highly valuable. Analytical thinking, problem-solving, and effective collaboration enhance your ability to develop and refine complex AI models. These skills ensure that AI solutions are robust, scalable, and aligned with organizational goals in a rapidly evolving technological landscape.

What are some common challenges faced by software engineers AI model training, and how can they be addressed?

Software Engineers focusing on AI model training often encounter challenges such as managing large datasets, ensuring data quality, and optimizing model performance. Addressing these issues typically involves close collaboration with data scientists, domain experts, and DevOps engineers to streamline the data pipeline and refine training processes. Staying up to date with the latest advancements in machine learning frameworks and tools can also help overcome technical hurdles. Regular code reviews and cross-functional meetings further support problem-solving and foster a productive work environment.

What is the difference between Software Engineer Ai Model Training vs Data Scientist?

AspectSoftware Engineer Ai Model TrainingData Scientist
Required CredentialsBachelor's in CS, related field; experience with ML frameworksBachelor's or higher in CS, statistics, or related field; strong analytical skills
Work EnvironmentDevelopment teams, AI labs, cloud platformsData analysis, research environments, business units
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, consulting

While both roles involve working with data and machine learning, Software Engineer Ai Model Training focuses on developing and optimizing AI models through coding and engineering practices. Data Scientists analyze data, build models, and generate insights. The roles often collaborate but differ in their core responsibilities and skill sets.

Can I get paid to train AI models?

Yes, software engineers and AI specialists can be paid to train AI models, especially in roles that involve developing, fine-tuning, and optimizing machine learning algorithms. These positions often require knowledge of programming languages like Python, experience with machine learning frameworks, and access to computational resources. Compensation varies based on experience, location, and the complexity of the models being trained.

How to become a software engineer AI model trainer?

To become a software engineer AI model trainer, you should have a strong background in computer science, programming skills in languages like Python, and experience with machine learning frameworks such as TensorFlow or PyTorch. Gaining knowledge in data preprocessing, model evaluation, and working with large datasets is essential, along with relevant certifications or advanced degrees in AI or related fields.

What cities near Callahan, FL are hiring for Software Engineer Ai Model Training jobs?

Cities near Callahan, FL with the most Software Engineer Ai Model Training job openings:

Software Engineer Ai Model Training jobs near you

Information Technology_USA - USA_Developer

Real Soft, Inc.

Jacksonville, FL • On-site

$100K - $136K/yr

Contractor

Re-posted 19 days ago

Job description

2 Candidate Submittal Slots, New High Level PolicyBill Rate - MSP Owner: Rob FintonLocation: White Plains, NY or Fort Lauderdale, FL - Position can be Onsite or RemoteDuration: 6 monthsGBaMS ReqID: 10914533Competencies: 10+ years experience requiredDigital : Machine LearningDigital : DevOpsQuick JD:Senior DevOps Engineer with deep expertise in designing, automating, and operating cloud-based AI/ML platforms.The ideal candidate will have hands-on experience building scalable, secure, and production-grade machine learning environments, with a strong focus on AWS SageMaker, MLOps practices, and modern cloud infrastructure.Experience with Generative AI platforms and services, including Amazon Bedrock, Azure OpenAI, vector databases, RAG architectures, and LLM deployment patterns.Familiarity with ML frameworks such as TensorFlow, PyTorch, MLflow, Kubeflow, or similar technologies.Experience supporting GPU-based workloads and optimizing infrastructure for AI model training and inference.This role will be instrumental in establishing and evolving the organization's AI/ML platform capabilities by delivering robust, automated, and secure cloud infrastructure that accelerates innovation while ensuring operational excellence.Role Summary : Senior DevOps Engineer - AI/ML Platform Engineering (AWS/Azure)This role will be instrumental in establishing and evolving the organization's AI/ML platform capabilities by delivering robust, automated, and secure cloud infrastructure that accelerates innovation while ensuring operational excellence.Senior DevOps Engineer with deep expertise in designing, automating, and operating cloud-based AI/ML platforms. The ideal candidate will have hands-on experience building scalable, secure, and production-grade machine learning environments, with a strong focus on AWS SageMaker, MLOps practices, and modern cloud infrastructure.Key Responsibilities & Qualifications• Extensive hands-on experience designing, implementing, and managing AI/ML infrastructure and MLOps platforms in AWS and/or Azure.• Strong expertise with AWS SageMaker, ML lifecycle management, model training and deployment pipelines, feature stores, model monitoring, and platform automation.• Proven experience building and supporting enterprise-scale MLOps ecosystems, including CI/CD pipelines, Infrastructure as Code (Terraform/CloudFormation/Bicep), containerization, and cloud-native architectures.• Experience integrating AI/ML platforms with modern data ecosystems, including technologies such as Snowflake, data lakes, streaming services, and analytics platforms.• Deep knowledge of cloud services including AWS ECS, EKS/Kubernetes, networking, security, IAM, observability, and high-availability architectures.• Responsible for enabling secure, scalable, resilient, and production-ready AI/ML platforms that support Data Science, Generative AI, and advanced analytics initiatives.• Serve as a trusted technical advisor to engineering, data science, and platform teams, providing architectural guidance, operational best practices, and real-time troubleshooting support.• Demonstrated ability to rapidly assess platform, infrastructure, and deployment challenges and recommend scalable, cost-effective, and secure solutions.• Strong understanding of DevSecOps principles, cloud governance, compliance requirements, and automation strategies for enterprise AI workloads.Excellent communication and collaboration skills, with the ability to bridge the gap between Data Science, Engineering, Operations, and Cloud Infrastructure teams.Preferred Experience• Experience with Generative AI platforms and services, including Amazon Bedrock, Azure OpenAI, vector databases, RAG architectures, and LLM deployment patterns.• Familiarity with ML frameworks such as TensorFlow, PyTorch, MLflow, Kubeflow, or similar technologies.• Experience supporting GPU-based workloads and optimizing infrastructure for AI model training and inference.

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