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AI/ML Engineer with Python experience

Jobs via Dice

Charlotte · On-site Full-time Senior Today

About the role

About

Dice is the leading career destination for tech experts at every stage of their careers. Our client, CA-One Tech Cloud Inc., is seeking the following.

Role

AI/ML Engineer with Python experience

Location

Onsite, Raleigh, NC (Local to Raleigh, NC Preferred)

Extra Remarks

Needs very strong hands-on experience with Python.

QUALIFICATIONS

  • 7+ years of experience building and delivering production-grade software, data, or AI solutions
  • 2-3 years of hands-on experience in AI/ML systems, including agentic workflows, LLM integrations, or intelligent automation
  • Hands-on experience with AWS cloud services and cloud-native architectures
  • BS in Engineering, Computer Science, Data Science, or related field required; advanced degree preferred

TECHNICAL SKILLS

  • Strong knowledge of software development methodologies (Agile, Waterfall) and modern engineering best practices
  • Strong programming skills in languages such as Python, Java/J2EE, JavaScript, SQL, and modern frameworks
  • Experience designing and building scalable systems, including APIs, microservices, and distributed architectures
  • Proficiency in CI/CD pipeline design, implementation, and maintenance, including automated testing, deployment, and release management
  • Experience with Git-based workflows and GitHub-based automation, including GitHub Actions and GitHub agent capabilities
  • Experience with AWS cloud services (e.g., EC2, S3, Lambda, RDS, EKS/ECS) and building cloud-native applications
  • Understanding of cloud architecture patterns, including scalability, resiliency, and cost optimization
  • Platform engineering experience, including building and maintaining reusable infrastructure, developer platforms, and self-service tooling (e.g. Infrastructure as Code using Terraform/CloudFormation)
  • Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes)
  • Proficiency in designing and implementing AI-powered systems, including LLM-based applications, agent frameworks, and workflow orchestration
  • Experience developing, evaluating, and deploying machine learning models (supervised, unsupervised, or deep learning)
  • Strong understanding of statistical analysis, experimentation, and model evaluation techniques
  • Experience with data processing and analysis tools (e.g., Pandas, Spark, or equivalent)
  • Advanced proficiency in data modeling, data manipulation, and optimization techniques
  • Strong knowledge of normalized and dimensional data modeling principles
  • Solid understanding of multiple data storage systems (relational, NoSQL, and data lake architectures)
  • Familiarity with MLOps practices, including model lifecycle management, monitoring, and observability
  • Knowledge of test-driven development and modern testing strategies across both data and application layers
  • Strong understanding of prompt engineering, evaluation strategies, and reliability considerations for AI systems
  • Strong research and problem-solving skills, including evaluating and applying emerging technologies
  • Ability to design, document, and implement complex system and data components
  • Strong communication skills, with the ability to work effectively across technical and non-technical audiences

ACCOUNTABILITIES

  • Design, develop, and deliver scalable solutions that integrate data, machine learning, and application logic.
  • Build and enhance AI-driven capabilities, including agentic workflows, LLM-based applications, and intelligent automation systems.
  • Develop and deploy solutions on AWS, ensuring scalability, reliability, and cost efficiency.
  • Contribute to platform engineering efforts, including improving developer experience, deployment pipelines, and infrastructure reuse.
  • Translate business problems into end-to-end solutions, including data exploration, feature engineering, modeling, and system integration.
  • Contribute to system and solution architecture to ensure scalability, reliability, and maintainability.
  • Partner with product, engineering, and business stakeholders to define and deliver impactful solutions.
  • Lead or contribute to moderately complex, cross-functional initiatives.
  • Write and review detailed technical specifications for system and data components.
  • Ensure adherence to best practices across coding, testing, data quality, and deployment.
  • Resolve complex technical and data-related issues across systems and models.
  • Mentor junior and mid-level team members across development, data, and AI practices.
  • Collaborate with internal and external technology resources to deliver solutions.
  • Stay current with emerging technologies in AI, cloud, and software systems, and recommend adoption where appropriate.
  • Support continuous improvement of development processes, data pipelines, and platform capabilities.
  • Serve as a key technical contributor and escalation point within the team.

Thanks & Regards,

Pankaj Singh - Team Lead Phone #

Skills

AWSAgileCloudFormationDockerEC2EKSECSGitGitHub ActionsInfrastructure as CodeJavaJ2EEJavaScriptKubernetesLambdaLLMMachine LearningMicroservicesPandasPythonRDSS3SparkSQLTerraformWaterfall

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