MLOps Engineer - MoneyLion

The role

You will design, build, and operate machine learning platform and infrastructure. You will work with Data Scientists, Data Engineers, and AI/ML Engineering teams to streamline ML workflows and improve system design for production-grade solutions.

What you will do

• Design, build, and maintain ML infrastructure and tooling for the full ML lifecycle.
• Develop and maintain CI/CD pipelines for ML models.
• Implement model deployment patterns including batch, real-time, and streaming.
• Build and operate monitoring and observability for ML systems.
• Partner with Data Scientists and ML Engineers to productize models.
• Collaborate with Data Engineering to integrate ML workloads into data platforms.
• Drive best practices in MLOps including versioning and experiment tracking.
• Contribute to security, compliance, and cost optimization of ML infrastructure.
• Provide technical guidance and support to cross-functional teams.

Required qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or related field, or equivalent practical experience.
• Solid programming skills in Python or similar languages.
• Hands-on experience with cloud platforms such as AWS, GCP, or Azure.
• Experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Experience implementing CI/CD pipelines for data or ML projects.
• Familiarity with ML frameworks and tooling such as scikit-learn, TensorFlow, PyTorch, MLflow, Kubeflow, SageMaker, or Vertex AI.
• Strong understanding of software engineering best practices including code reviews, testing, logging, monitoring, and documentation.
• Good collaboration and communication skills with experience working in cross-functional teams.

Nice to have

• Experience in a dedicated MLOps / ML Platform / ML Infrastructure role across multiple model lifecycles.
• Experience building or supporting feature stores, model registries, and experiment tracking systems.
• Exposure to streaming and near-real-time data processing such as Kafka, Kinesis, or Pub/Sub.
• Experience with observability stacks such as Prometheus, Grafana, ELK/EFK, or Datadog.
• Familiarity with LLM / GenAI workloads and associated tooling.

Benefits

• Flexible working options
• Time off
• Competitive pay
• Benefits
• Well-being programs

Before you apply

• Online Technical Assessment
• TA Screening Call
• Live Technical Assessment
• Final Interview

About the company

Gen is a global company dedicated to powering Digital Freedom through brands including Norton, Avast, LifeLock and MoneyLion. They deliver cybersecurity, online privacy, identity protection and financial wellness solutions to nearly 500 million users.