Point Wild (Formerly Pango Group)
ML Ops Engineer
Point Wild (Formerly Pango Group)Ukraine12 days ago
Full-timeEngineering, Information Technology
Point Wild helps customers monitor, manage, and protect against the risks associated with their identities and personal information in a digital world. Backed by WndrCo, Warburg Pincus and General Catalyst, Point Wild is dedicated to creating the world's most comprehensive portfolio of industry-leading cybersecurity solutions. Our vision is to become THE go-to resource for every cyber protection need individuals may face - today and in the future.

Join us for the ride!

The Lat61 Mission:

The Lat61 platform will power the next generation of cybersecurity and AI-enabled decision-making. As an ML Ops Engineer on this team, you will help deliver:

  • ML Infrastructure at Scale: Building and maintaining AWS-based ML infrastructure (e.g., SageMaker, S3, Lambda, Batch) to support production-grade AI workloads.
  • Model Deployment & CI/CD: Designing and operating CI/CD pipelines for ML models, including versioning, containerization, and automated retraining.
  • Monitoring & Observability: Implementing logging, metrics, and alerting to ensure deployed models are reliable, efficient, and production-ready.
  • Collaboration Across Teams: Partnering with AI and Data Engineers to integrate models, datasets, and features into scalable, cloud-native environments.

About the Role:

As an ML Ops Engineer, you will play a critical role in building and maintaining the infrastructure, pipelines, and tooling that enable AI models to be deployed, scaled, and monitored in production. You'll collaborate closely with AI and Data Engineering teams to ensure smooth handoff from experimentation to production.

Day to Day:

  • Model Deployment & MLOps: Own CI/CD workflows for ML models, including environment setup, model versioning, containerization, and monitoring.
  • AWS ML Infrastructure: Stand up and manage AWS-based ML infrastructure (e.g., S3, Lambda, Batch, SageMaker, CloudWatch).
  • Production Monitoring: Implement observability, logging, and automated retraining triggers to keep deployed models reliable and efficient.
  • Support AI Engineers: Provide scalable training environments, deployment pipelines, and runtime infra for research-to-production workflows.
  • Data Integration (Light): Collaborate with Data Engineers and contribute where needed to dataset versioning, feature store enablement, or lightweight transformations.
  • Scaling PoCs to Production: Help transition AI prototypes into robust, production-ready services that can scale across products.

What you bring to the table:

  • Hands-on experience with AWS ML infrastructure (SageMaker, S3, Lambda, etc.), containerization, and automation.
  • Skilled at setting up workflows for model deployment, versioning, retraining, and monitoring.
  • Proficiency in Python and SQL for scripting, automation, and lightweight data handling.
  • Experience with logging, metrics, and alerting for ML models in production.
  • Comfortable working alongside AI engineers and data engineers to support end-to-end ML lifecycle.
  • Able to balance rapid prototyping with building scalable, maintainable systems.

As part of Point Wild, you will:

Solve real customer problems. Point Wild's point solutions allow consumers to address their immediate cyber protection needs. Our mandate is to continuously anticipate our customers' evolving digital security needs to create best-in-class solutions aimed at keeping them safe.

See your impact. We are a scrappy, nimble organization where individual contributions are needed and valued. You will see your impact every day.

Accelerate your career. As we expand, you will have the opportunity to learn new technologies, products, and markets in a fast-paced, growth-oriented environment.

Most importantly, you'll get to work with other talented people at a company where people matter. If you want to put your fingerprint on an organization and leapfrog your growth, this is the place for you.

In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on race, color, ancestry, national origin, religion, age, gender, marital domestic partner status, sexual orientation, gender identity, disability status, or veteran status. Above and beyond discrimination or harassment based on "protected categories," Point Wild is committed to being an inclusive community where all feel welcome. Whether blatant or hidden, barriers to success have no place at Point Wild.

Important privacy information for United States based job applicants can be found here.

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