✦ Luna Orbit — AI & Machine Learning

Staff Machine Learning Engineer

at Angi

📍 Remote, US Remote 💰 $200K – $280K USD / year Posted March 04, 2026
Salary $200K – $280K USD / year
Type Not Specified
Experience senior
Exp. Years Not specified
Education Not specified
Category AI & Machine Learning

A technical leadership role focused on developing and deploying advanced machine learning models to improve marketplace algorithms and user experience.

  • Lead ML model development
  • Design scalable deployment systems
  • Collaborate with cross-functional teams
  • Innovate on product features
  • Optimize model performance

Involves building scalable ML models, deploying AI solutions, and leveraging MLOps practices using tools like TensorFlow, PyTorch, Kubernetes, and Docker.

The ideal candidate is a senior machine learning engineer with extensive experience in developing and deploying AI models at scale. They possess strong software engineering skills and a deep understanding of marketplace algorithms, search ranking, and recommendation systems.

Machine LearningAIModel DevelopmentModel DeploymentSoftware Engineering
Recommendation SystemsSearch RankingScalable SystemsLow LatencyMLOps
PythonTensorFlowPyTorchKubernetesDockerMLflowCloud Platforms (AWSGCPAzure)
Machine LearningAIModel DevelopmentModel DeploymentMLOpsSoftware EngineeringSearch RankingRecommendation SystemsScalable SystemsLow Latency
Machine LearningAIModel DevelopmentModel DeploymentMLOpsSoftware EngineeringSearch RankingRecommendation SystemsScalable SystemsLow Latency
CollaborationLeadershipProblem-solvingInnovationCommunication
Industry SaaS, Technology, Home Services
Job Function Developing and deploying machine learning models for marketplace enhancement
Machine LearningAIModel DevelopmentModel DeploymentMLOpsSoftware EngineeringSearch RankingRecommendation SystemsScalable SystemsLow LatencyPythonTensorFlowPyTorchKubernetesDockerMLflow

Lack of experience in MLOps or scalable ML systems, No background in software engineering, Unable to collaborate with cross-functional teams

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