RADAR
Machine Learning Engineer
Sunnyvale, CA
Sponsorship not specified$195k-$264kDetected 11 days ago
PythonGitSQLAWSAzureCI/CDKafkaMachine LearningPyTorchscikit-learnSparkAirflowData ScienceMLOpsAI OrchestrationStatisticsCustomer SuccessSensorsTest AutomationResearchCommunicationCollaboration
About the role
- RADAR is one of the best-funded companies in retail technology, backed by a recent Series B financing at a $1 billion valuation.
- Inventory accuracy is only the beginning.
- We believe RADAR can become foundational infrastructure for the physical economy, powering new AI-driven commerce experiences across retail and beyond.
Responsibilities
- Build and scale ML infrastructure: Design and maintain scalable, reliable and efficient production pipelines for feature engineering, training, prediction and model serving using tools including Airflow, Big Query and Kubeflow
- Drive model performance: Train, validate and deploy high-quality ML models, applying advanced techniques in feature selection, hyperparameter tuning and model architecture choices to improve the accuracy of our products
- Accelerate ML development: Optimize feature engineering pipelines for performance and scalability while collaborating with Data Science to research, develop, and deploy new features that improve model accuracy
- 5+ years building production ML systems at scale, including feature engineering, training, deployment, and monitoring
- We build with deep respect for our end users, listening closely to their feedback and needs.
- Train, validate and deploy high-quality ML models, applying advanced techniques in feature selection, hyperparameter tuning and model architecture choices to improve the accuracy of our products
- Optimize feature engineering pipelines for performance and scalability while collaborating with Data Science to research, develop, and deploy new features that improve model accuracy
Requirements
- Strong proficiency in Python and ML frameworks (scikit-learn, PyTorch, XGBoost)
- Hands-on experience with cloud ML platforms (AWS SageMaker, Vertex AI, or Azure ML)
- Expertise in big data processing including SQL optimization and distributed computing (Spark/Dask)
- Production experience with workflow orchestration tools (Airflow, Dagster, Prefect)
- Proficiency with version control (Git) and CI/CD practices
- Experience with real-time streaming data (Kafka, Flink, Pub/Sub.)
- Bachelor's degree in Computer Science, Statistics, or related field
- Experience with MLOps tools (MLflow, Weights & Biases, etc.)
Compensation
- The expected base salary range for this position is $195,000 - $264,000.
- The pay range listed for this position is a good faith and reasonable estimate of the range of possible base compensation at the time of posting.
Benefits
- Implement comprehensive model monitoring, automated training pipelines, and observability solutions to maintain model health and performance
- You will also be eligible to receive other benefits including: equity, comprehensive medical and dental coverage, life and disability benefits, 401k plan, flexible time off, and paid parental leave.
- We are looking for a Machine Learning Engineer to help build and develop our ML capabilities at RADAR.
- Individual pay is determined by work location and additional factors, including job-related skills, experience and relevant education or training.
- This is a hybrid role based in our Sunnyvale, CA location with a flexible hybrid work schedule of 2-3 days in the office.
Company info
- E-commerce got real-time data infrastructure decades ago. Physical stores still have not. RADAR is changing that.
- RADAR is building the data infrastructure layer for the physical world, starting with retail. Our hardware-enabled SaaS platform uses proprietary overhead sensors, software, and AI-powered analytics to locate every product in a store, continuously, down to the fixture. We are deployed across 1,400+ stores with retailers including American Eagle Outfitters and Old Navy, processing tens of billions of real-world events every day, delivering 99%+ accuracy in complex, noisy environments - at fleet scale.
- RADAR is one of the best-funded companies in retail technology, backed by a recent Series B financing at a $1 billion valuation. Inventory accuracy is only the beginning. We believe RADAR can become foundational infrastructure for the physical economy, powering new AI-driven commerce experiences across retail and beyond.
- Join us if you want to work on a large, unsolved, technically challenging problem with an ambitious team building category-defining technology.
- E-commerce got real-time data infrastructure decades ago.
- Physical stores still have not.
- RADAR is changing that.
- RADAR is building the data infrastructure layer for the physical world, starting with retail.
- Our hardware-enabled SaaS platform uses proprietary overhead sensors, software, and AI-powered analytics to locate every product in a store, continuously, down to the fixture.
- We are deployed across 1,400+ stores with retailers including American Eagle Outfitters and Old Navy, processing tens of billions of real-world events every day, delivering 99%+ accuracy in complex, noisy environments - at fleet scale.
- Mission-Driven: We're transforming retail with cutting-edge technology and building something that truly matters.
This listing is sourced directly from RADAR's careers page and normalized into a canonical job model.