DevOps Engineer with AI Ops Experience

Syntricate Technologies

Atlanta, GA

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JOB DETAILS

JOB TYPE

Full-time

SKILLS

A/B Testing, Access Control, Amazon Web Services (AWS), Ansible, Apache, Artificial Intelligence (AI), Automation, Bash Scripting, Best Practices, Cloud Architecture, Cloud Computing, Communication Skills, Computer Programming, Continuous Deployment/Delivery, Continuous Integration, Cryptography, Data Management, Data Modeling, Data Processing, Data Science, DevOps, Docker, GCP (Good Clinical Practices), Identify Issues, Jenkins, LinkedIn, Machine Learning, Mentoring, Microsoft Windows Azure, Operational Support, Performance Analysis, Performance Metrics, Performance Modeling, Problem Solving Skills, Production Systems, Python Programming/Scripting Language, Quality Assurance Methodology, Regulatory Compliance, Resource Management, Risk Management, Scripting (Scripting Languages), Software Development, Systems Reliability, Team Player, Test Automation, Training/Teaching

LOCATION

Atlanta, GA

POSTED

30+ days ago

Hi, We are looking for a DevOps Engineer with AI experience. Please let me know, if interested. Role: DevOps Engineer with AI Ops Experience Location: Atlanta, GA (5 Days onsite) W2 Contract Only Job Description: 5+ years of experience in DevOps engineering, with at least 3 years specializing in AI Ops or supporting ML/AI model deployment and infrastructure. Proven experience in designing, implementing, and managing CI/CD pipelines and ML Ops frameworks to automate AI/ML workflows. Technical Skills: Proficiency in cloud platforms (AWS, GCP, Azure) with hands-on experience in deploying AI/ML models and utilizing AI/ML services (e.g., AWS SageMaker, Google AI Platform). Strong skills in containerization and orchestration tools such as Docker and Kubernetes, especially for deploying machine learning models at scale. Experience with infrastructure-as-code tools like Terraform, CloudFormation, or Ansible to manage and provision cloud and on-premise environments. Proficiency in CI/CD tools (e.g., Jenkins, GitLab CI, CircleCI) to build automated pipelines for AI/ML model training, testing, and deployment. Solid understanding of monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack) for model performance tracking and infrastructure observability. Strong programming and scripting skills in Python, Bash, and YAML for automating workflows and integrating services. AI Ops and MLOps Skills: Experience with MLOps best practices, including model versioning, automated retraining, and model governance for reliable and reproducible AI pipelines. Hands-on experience with model monitoring tools (e.g., MLflow, Kubeflow, or TFX) to track model performance, drift, and retraining needs. Familiarity with data pipelines and orchestration tools (e.g., Apache Airflow, Prefect) for managing data and model workflows. Knowledge of model deployment strategies (e.g., blue-green deployments, canary releases) to ensure reliable AI/ML model deployment with minimal downtime. Experience with A/B testing and experiment tracking to evaluate model performance in production and measure the impact on business KPIs. DevOps and Automation Skills: Ability to design and manage scalable infrastructure to support machine learning workloads, ensuring cost efficiency, performance, and security. Proficiency in automating testing and deployment processes for data and model pipelines to support fast, reliable releases. Familiarity with serverless architectures and cloud-native tools for AI, allowing for flexible and efficient resource management. Experience with security best practices, including role-based access control, data encryption, and compliance requirements for data-sensitive applications. Communication and Collaboration Skills: Excellent communication skills with the ability to collaborate closely with data scientists, ML engineers, and software development teams. Proven ability to document infrastructure, CI/CD pipelines, and MLOps processes, ensuring transparency and knowledge sharing across teams. Strong problem-solving skills and a proactive approach to troubleshooting, particularly in managing and resolving deployment and performance issues. Ability to train and mentor team members on MLOps tools, best practices, and model deployment techniques. Additional Qualifications: Experience with data security and governance standards, especially related to machine learning applications in regulated industries. Familiarity with AI ethics and compliance, including model fairness, transparency, and risk management. Knowledge of advanced monitoring and alerting tools and techniques to ensure the reliability of AI systems in production. Strong interest in staying up-to-date on the latest advancements in MLOps and AI Ops to continuously improve infrastructure and processes Thanks & Regards, Sushil Kumar Kwatra Assistant Manager-Recruitment | Syntricate Technologies Inc. Direct: 781-787-2012 | Email: sushil.k@syntricatetechnologies.com | Web: www.syntricatetechnologies.com We're hiring! connect with us on LinkedIn and visit our Jobs Portal Minority Business Enterprise (MBE) Certified | E-Verified Corporation | Equal Employment Opportunity (EEO) Employer This e-mail message may contain confidential or legally privileged information and is intended only for the use of the intended recipient(s). Any unauthorized disclosure, dissemination, distribution, copying or the taking of any action in reliance on the information herein is prohibited. Please notify the sender immediately by email if you have received this email by mistake and delete this e-mail from your system. You have received this email as we have your email address shared by you or from one of our data sources or from our member(s) or subscriber(s) list. If you do not want to receive any further emails or updates, please reply and request to unsubscribe.

About the Company

Syntricate Technologies

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