Machine Learning Engineer

Job not on LinkedIn

October 23

🏄 California – Remote

Although this job is listed in California, this company may be open to hiring remote in other states.

💵 $120k - $190k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

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RADAR

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Retail • Hardware • SaaS

RADAR is a technology company that transforms inventory management in retail through advanced RFID and computer vision solutions. By providing real-time tracking and unprecedented location accuracy, RADAR enables retailers to know exactly what's in their stores and where it is at all times. Their autonomous checkout feature allows customers to shop without waiting in lines, streamlining the purchasing process. With a focus on enhancing operational efficiency, RADAR's innovative technology empowers retailers to optimize stock management and improve customer engagement.

51 - 200 employees

Founded 2013

🛒 Retail

🔧 Hardware

☁️ SaaS

📋 Description

• 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 • Champion best practices: Apply CI/CD principles including automated testing, model validation, and deployment strategies

🎯 Requirements

• 2+ 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.)

🏖️ Benefits

• equity • comprehensive medical and dental coverage • life and disability benefits • 401k plan • flexible time off • paid parental leave