Company Overview:

GetReal Labs is the world’s leading authority on malicious manipulated content and deepfake detection, offering advanced solutions to authenticate content and combat deception. Our technology serves corporations, financial institutions, media organizations, and government agencies. Incubated by Ballistic Ventures, the venture capital firm dedicated exclusively to funding and incubating entrepreneurs and innovations in cybersecurity, GetReal Labs was co-founded by Hany Farid, the go-to source for media forensics.

Role Overview:

As an MLOps Engineer at GetReal Labs, you will be responsible for developing, deploying, and maintaining the infrastructure and tools that enable the seamless operation of machine learning (ML) models in production environments. You will work closely with data scientists, ML engineers, and software developers to ensure that ML models are integrated effectively and perform reliably at scale. This role requires a strong background in both software engineering and machine learning operations, as well as a passion for building robust and scalable ML systems.

Key Responsibilities:

• Infrastructure Development: Design, build, and maintain the infrastructure required for deploying and managing ML models, including cloud-based and on-premises solutions.
• Model Deployment: Develop and implement processes and tools for the continuous integration and deployment (CI/CD) of ML models into production environments.
• Monitoring and Maintenance: Monitor the performance of deployed models, troubleshoot issues, and implement improvements to ensure optimal performance and reliability.
• Collaboration: Work closely with data scientists, ML engineers, and software developers to understand model requirements and ensure seamless integration into production systems.
• Automation: Automate ML workflows, including data preprocessing, model training, and model deployment, to streamline the ML lifecycle.
• Security and Compliance: Ensure that ML systems and data adhere to security and compliance standards.
• Documentation: Maintain clear and thorough documentation of infrastructure, processes, and tools for knowledge sharing and future reference.
• Innovation: Stay up-to-date with the latest advancements in MLOps and contribute to the ongoing improvement of our ML infrastructure and practices.

Qualifications:

• Educational Background: Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Experience: 3+ years of experience in ML Ops, DevOps, or related roles.
• Skills:
  • Proficiency in programming languages such as Python and TypeScript
  • Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their ML services.
  • Experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch).
  • Hands-on experience with deploying ML models on AWS using services such as SageMaker, ECS, EKS, Lambda, and more.
  • Experience with Terraform or other infrastructure-as-code tools.
  • Familiarity with data engineering concepts and tools (e.g., Spark, Kafka).
  • Knowledge of machine learning lifecycle management tools (e.g., MLflow, Kubeflow).
  • Strong understanding of CI/CD pipelines and tools (e.g., Jenkins, GitLab CI).
  • Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
  • Knowledge of monitoring and logging tools (e.g., DataDog, Grafana).
  • Excellent problem-solving skills and attention to detail.
  • Strong communication and collaboration skills.
  • Certification in AWS a plus (e.g., AWS Certified Solutions Architect, AWS Certified Machine Learning – Specialty)

Compensation and Benefits:

• Competitive salary and stock options
• Comprehensive health, dental, and vision insurance
• Generous paid time off and company holidays
• Professional development opportunities
• Hybrid work environment, with 3 days per week expected in office in Atlanta, GA or Austin, TX

The salary range for this position is $135,000 to $165,000 depending on the candidate’s skills, experience, and qualifications. In addition to cash compensation, this role is eligible for a stock option grant.