MLOps Engineer

4 days ago

Bengaluru, Karnataka, India FaceFirst Full time ₹ 6,00,000 - ₹ 12,00,000 per year

Company Description

FaceFirst is a global leader in developing advanced face matching systems that combine artificial intelligence and human oversight. The company specializes in providing services that prioritize life safety, loss prevention, and privacy protection. FaceFirst's innovative solutions are designed for precision and reliability, supporting clients in a variety of industries. The organization is committed to leveraging technology to enhance security and safety across the globe.

Role Description

This is a full-time, on-site role for an MLOps Engineer based in Bengaluru. The MLOps Engineer will be responsible for maintaining and optimizing machine learning operations workflows. This includes designing, deploying, and managing scalable ML models, ensuring efficient workflows, and collaborating with cross-functional teams. Day-to-day responsibilities may also involve enhancing deployment pipelines, monitoring system performance, and implementing innovative solutions to improve overall efficiency.

Key Responsibilities

  • Work with MLEs to support the deployment, scaling, and monitoring of ML models.
  • Build and maintain automated ML pipelines for training, validation, deployment, and monitoring.
  • Monitor system and model performance, troubleshoot issues, and optimize infrastructure for cost and efficiency.
  • Manage cloud infrastructure on Microsoft Azure and on-prem servers.
  • Set up and maintain VPNs and networking configurations to enable secure, reliable access for teams working across multiple locations.
  • Implement and enforce security best practices for both cloud and on-premises environments.
  • Document operational processes, networking setups, and security protocols.

Required Qualifications

  • 1-4 (Flexible) years of experience in MLOps, DevOps, or related roles that expose you to their practices.
  • Understanding of networking concepts including VPN setup, firewalls, routing, and secure connectivity for distributed teams.
  • Familiarity with CI/CD tools and pipelines.
  • Familiarity with SQL and Relational DB's.
  • Familiarity with ML frameworks, specifically PyTorch and scikit-learn.
  • Experience with Microsoft Azure services (Azure ML, Azure DevOps, AKS, Azure Storage).
  • Experience managing on-premises servers and hybrid cloud environments.
  • Experience with containerization tools like Docker and Kubernetes.
  • Strong Python and Bash scripting skills.
  • Strong problem-solving skills and ability to work collaboratively in a team environment.

Preferred (Not Required)

  • Understanding data engineering and security best practices.
  • Familiarity with data visualization tools and analytics.
  • Familiarity with GCP.
  • Experience with ML Training and Development
  • Experience with other languages and frameworks (React/Angular, Go, C++, etc.)

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