Machine Learning Engineer

• 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
• Ensure reliability: Implement comprehensive model monitoring, automated training pipelines, and observability solutions to maintain model health and performance
• 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
• Champion best practices: Apply CI/CD principles including automated testing, model validation, and deployment strategies

Do you have experience in Version control systems?, Do you have a Bachelor’s degree?, * 5+ years building production ML systems at scale, including feature engineering, training, deployment, and monitoring

• 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.)

3.73.7 out of 5 stars Sunnyvale, CA Hybrid work $140,000 - $220,000 a year, Pulled from the full job description

• Paid parental leave
• Parental leave
• 401(k)
• Health insurance
• Dental insurance, * Mission-Driven: We’re transforming retail with cutting-edge technology and building something that truly matters.
• Collaborative Team: We thrive on curiosity, shared goals, and solving complex problems together.
• High Impact: You’ll make meaningful contributions from day one and help shape the future of our product and company.
• Clear Communication: We value honesty, humility, and respectful dialogue-everyone’s voice matters.
• Balanced Lives: We work hard, but not at the expense of well-being. We respect time, boundaries, and life outside of work.
• Diverse Perspectives: We believe better ideas come from diverse backgrounds, experiences, and viewpoints.
• Empathy-Driven Design: We build with deep respect for our end users, listening closely to their feedback and needs., At RADAR, your base pay is one part of your total compensation package. The expected base salary range for this position is $140,000 - $220,000. Individual pay is determined by work location and additional factors, including job-related skills, experience and relevant education or training.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. 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.

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.