✦ Luna Orbit — AI & Machine Learning

Senior Machine Learning Engineer

at FINGERPRINT

📍 Remote, US Remote 💰 $204K – $235K USD / year Posted March 07, 2026
Salary $204K – $235K USD / year
Type Full-Time
Experience senior
Exp. Years 6-10 years
Education BS/MS in Computer Science, Data Science, or a related field
Category AI & Machine Learning

A senior ML engineer role focused on designing, building, and maintaining scalable ML solutions and infrastructure for fraud detection.

  • Design and maintain ML systems
  • Collaborate with data scientists and engineers
  • Build scalable ML infrastructure
  • Implement MLOps practices
  • Ensure model reproducibility and monitoring

Involves working with ML systems, data pipelines, model deployment, CI/CD, and observability tools, primarily using Python and cloud-based platforms.

The ideal candidate is a senior ML engineer with 6+ years of experience in designing and maintaining production-grade ML systems and infrastructure. They possess strong collaboration skills and expertise in ML deployment, data pipelines, and scalable infrastructure.

BS/MS in Computer ScienceData Scienceor related field6-10 years of experience as an ML EngineerExperience establishing ML systemsExperience with ML infrastructureExperience with data pipelinesExperience with model deploymentExperience with CI/CDExperience with observability and retrainingExperience with versioning ML modelsExperience with performance optimization
Experience with MLOps toolsExperience with cloud platforms (AWSGCPAzure)Experience with containerization (DockerKubernetes)Experience with open-source ML toolsExperience with model monitoring
PythonDockerKubernetesML frameworks (TensorFlowPyTorch)CI/CD toolsGitCloud platforms (AWSGCPAzure)
Machine LearningMLData PipelinesModel DeploymentCI/CDPythonData ScienceData EngineeringML OpsModel Serving
Machine LearningMLML systemsML infrastructureData PipelinesModel DeploymentCI/CDObservabilityReproducibilityAutomationPythonData ScienceData EngineeringML OpsModel Serving
collaborationcommunicationleadershipproblem-solvingscalabilityreliabilityteamworkcross-functional collaboration
Industry SaaS / Technology / Fraud Detection
Job Function Developing and maintaining production-grade ML solutions and infrastructure
Machine LearningMLML systemsML infrastructureData PipelinesModel DeploymentCI/CDObservabilityReproducibilityAutomationPythonData ScienceData EngineeringML OpsModel Serving

Less than 6 years of ML engineering experience, Lack of experience with ML infrastructure and deployment, No experience with data pipelines or CI/CD, No background in Data Science or related fields

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