| Lead DevOps at San Antonio, Texas, USA |
| Email: [email protected] |
| From: Satyajit Nayak, tekinspirations [email protected] Reply to: [email protected] Job Description - Title: Lead DevOps/MLOps Engineer MUST have Oil and Gas experience, AZ-400 Certification and LEAD experience. The client would also like all candidates to complete a Spark Hire one-way video interview. Domain: Oil and Gas Bill rate: Send your best candidates and we will discuss Location: San Antonio, TX/Denver, CO (preference given to candidates currently in either city) VISA: All are accepted Duration: 12-month open end contract Work Location: San Antonio, TX/Denver, CO Requirements: Education: Bachelors Degree in Computer Science, Engineering, or a related field. Experience: 5+ years of experience in DevOps, MLOps, or a related field. Azure DevOps and AzureML experience. Technical Expertise: Proficiency in cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes). Strong programming skills in Python, Bash, PowerShell or other scripting languages. Experience with infrastructure as code (Terraform, ARM). Tool Proficiency: Familiarity with CI/CD tools (Jenkins, GitHub Actions, ADO Pipelines). Knowledge of machine learning frameworks (TensorFlow, PyTorch) and data processing tools (Apache Spark, Airflow). Problem-Solving: Excellent problem-solving and analytical skills, with a focus on delivering practical and efficient solutions. Preferred Experiences: Advanced Analytics Tools: Experience with advanced analytics tools and methodologies, including monitoring and logging solutions (Azure Monitor, Prometheus, Grafana). Agile Methodologies: Experience working in Agile development environments. Communication: Strong verbal and written communication skills, capable of articulating complex technical concepts to both technical and non-technical stakeholders. Team Collaboration: A collaborative mindset with a track record of working effectively within diverse teams. Other Qualifications: AZ-400 DevOps Engineer Certification is desired. Experience with Data Science and Machine Learning teams is desired. Position Summary We are seeking an experienced and highly motivated DevOps / MLOps Engineer Lead to join our dynamic Data Science and AI team. In this role, you will be pivotal in creating and maintaining robust, scalable, and efficient CI/CD pipelines for our machine learning models and data processing workflows. You will collaborate with cross-functional teams to streamline and automate the end-to-end deployment processes, ensuring our AI/ML initiatives are delivered with high quality and speed. Key Responsibilities Develop and Implement CI/CD Pipelines: Design, build, and maintain continuous integration and deployment pipelines for machine learning models and data processing workflows. Automation and Orchestration: Develop and continuously improve automation solutions to enable teams to build and deploy code efficiently and consistently. Promote DevSecOps Principles: Foster a DevSecOps culture across the Analytics & Innovation organization, ensuring security is integrated into the development process. Lifecycle Streamlining: Streamline the data science and development lifecycles by identifying and resolving pain points and productivity barriers. Collaboration: Work closely with data scientists, data engineers, and software developers to integrate and deploy machine learning models into production. Monitoring and Troubleshooting: Implement monitoring and logging solutions to ensure the health and performance of deployed models and systems, and troubleshoot issues as they arise. Security and Compliance: Ensure the security and compliance of data and infrastructure, adhering to industry best practices and regulatory requirements. Documentation: Maintain comprehensive documentation of systems, processes, and workflows to facilitate knowledge sharing and collaboration. Desired Skills and Experience It will ask the candidates questions about their experience and the questions are below. Camera and microphone are on - a suit and tie are not necessary at all, but a collared shirt and clean background go a long way. This should be a natural response - so please do not read off of a resume. As soon as this is completed I will give the candidates a call, talk to them about the job requirements, and submit them. Spark Hire Questions : CI/CD Pipeline Experience: Can you describe a time when you designed and implemented a CI/CD pipeline specifically for machine learning models What tools did you use, and what were the biggest challenges you faced Cloud Platform Proficiency: How would you rate your experience with cloud platforms like AWS, Azure, or GCP Can you provide specific examples of projects where you leveraged these platforms to deploy machine learning models or data processing workflows Containerization and Orchestration: How proficient are you with containerization technologies like Docker and Kubernetes Have you used these tools to manage production environments for machine learning applications Infrastructure as Code: Could you provide an example of a project where you utilized infrastructure as code tools such as Terraform or ARM How did this approach benefit the deployment process DevSecOps Practices: How have you integrated security into the development lifecycle in past roles Can you give examples of how you've promoted DevSecOps principles within a team Monitoring and Troubleshooting: Describe your experience with monitoring and logging solutions such as Azure Monitor, Prometheus, or Grafana. How have you used these tools to ensure the health and performance of deployed models Team Collaboration: This role involves working closely with data scientists, data engineers, and software developers. How do you ensure effective communication and collaboration in a cross-functional team Agile Methodologies: Have you worked in Agile environments before Can you describe your role within Agile teams and how you contributed to the iterative development and deployment processes Problem-Solving Skills: Can you share an instance where you identified and resolved a significant bottleneck in the data science or development lifecycle What approach did you take, and what was the outcome Communication Skills: How do you explain complex technical concepts to non-technical stakeholders Can you give an example of how youve successfully communicated technical challenges or solutions to a diverse audience Regards, Satyajit nayak Sr. Technical Recruiter TEK Inspirations LLC | 13573 Tabasco Cat Trail, Frisco, TX 75035 E : [email protected] Linkedin: linkedin.com/in/satyajeet-nayak-85751625b Keywords: continuous integration continuous deployment artificial intelligence machine learning information technology golang Arizona Colorado Texas Lead DevOps [email protected] |
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| Tue Aug 27 05:02:00 UTC 2024 |