MLOps Engineer

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We’re hiring passionate builders to shape the future of industrial intelligence.

Looking forDevOps/MLOps Engineer with 7 years plus of experience.

• Cloud Infrastructure Management:
  Design, implement, and manage cloud-based infrastructure on AWS and Azure, ensuring optimal scalability, performance, and security.
• CI/CD Pipeline Development:
  Develop and maintain CI/CD pipelines using Git Hub Actions for automated code deployments and testing.
• System Monitoring and Incident Management:
• Implement and configure Datadog for comprehensive system monitoring.
• Develop and maintain Datadog dashboards to visualize system performance and metrics.
• Set up proactive alerts in Datadog to detect and respond to incidents swiftly, ensuring high system reliability and uptime.
• Conduct root cause analysis of incidents and implement corrective actions using Datadog insights.
• Collaboration with AI Teams:
  Work closely with AI teams to support the operational aspects of LLMs, including deployment strategies and performance tuning.
• Infrastructure as Code (IaC):
  Implement IaC using tools like Terraform or AWS Cloud Formation to automate infrastructure provisioning and management.
• Container Orchestration:
  Manage container orchestration systems such as Kubernetes or AWS ECS.
• Operational Support for LLMs:
  Provide operational support for LLMs, focusing on performance optimization and reliability.
• Scripting and Automation:
  Utilize scripting languages such as Python and Bash for automation and task management.
• Security and Compliance:
  Ensure compliance with security standards and best practices, implementing robust security measures.
• Documentation:
  Document system configurations, procedures, and best practices for internal and external stakeholders.
• Dev Ops Collaboration :
  Work with development teams to optimize deployment workflows, introduce best practices forDevOps, and improve overall efficiency.
• Technology and Industry Awareness:
  Stay up-to-date with emerging technologies and industry trends to suggest improvements and upgrades.

• Extensive experience with AWS and Azure cloud platforms.
• Proficiency in developing CI/CD pipelines using Git Hub Actions.
• Strong experience with Datadog for system monitoring, including implementation, configuration, and maintenance.
• Demonstrated ability to create and maintain Datadog dashboards for performance visualization.
• Proven expertise in setting up alerts and conducting incident response with Datadog.
• Hands-on experience with container orchestration systems such as Kubernetes or AWS ECS.
• Proficiency in Infrastructure as Code (IaC) tools like Terraform or AWS Cloud Formation.
• Familiarity with operational aspects of Large Language Models (LLMs) is highly desirable.
• Strong scripting skills in Python, Bash, or similar languages.
• In-depth knowledge of security standards and best practices.
• Proven ability to work collaboratively with development and AI teams.
• Commitment to staying current with industry trends and emerging technologies

Must Haves: AWS ECS, S3, Lambda, Cloud Front, Github actions, Git, Python, Terraform, VPC, API Gateway