Machine Learning Engineer

About The Company

At RADAR, we are revolutionizing the physical retail landscape through innovative technology solutions. With over $104 million raised from leading investors, retailers, and strategic partners, we collaborate with some of the world's most prominent billion-dollar global retailers. Our mission is to create an in-store experience where every product and every individual can be precisely located in real time. Our platform leverages RFID and AI technologies to deliver hyper-accurate product visibility and automation at scale. From real-time inventory management to seamless checkout processes, our solutions empower retailers to optimize operations, minimize losses, and enhance both employee and customer experiences. As a fast-growing, mission-driven startup, we foster a culture of bold ideas, collaboration, and impactful work, aiming to reshape the retail environment and expand our influence beyond.

About The Role

We are seeking a skilled Machine Learning Engineer to join our team at RADAR. In this role, you will be instrumental in developing and scaling our machine learning capabilities, working closely with cross-functional teams including product management, customer success, engineering, data science, and research. Your primary focus will be on building robust ML infrastructure, enhancing model performance, and ensuring the reliability of deployed models. You will be responsible for designing scalable production pipelines, optimizing feature engineering processes, and deploying high-quality models that improve our platform’s accuracy and efficiency. Additionally, you will champion best practices in MLOps, automate workflows, and implement monitoring solutions to maintain model health. This position offers an exciting opportunity to contribute to cutting-edge retail technology and to be part of a dynamic, innovative environment where your work directly impacts the future of in-store experiences.

Qualifications

• 2+ years of experience building production ML systems at scale, including feature engineering, training, deployment, and monitoring
• Proficiency in Python and machine learning frameworks such as scikit-learn, PyTorch, XGBoost
• Hands-on experience with cloud ML platforms like AWS SageMaker, Google Vertex AI, or Azure ML
• Expertise in big data processing, including SQL optimization and distributed computing with Spark or Dask
• Experience with workflow orchestration tools such as Airflow, Dagster, or Prefect
• Strong understanding of version control systems (Git) and CI/CD practices
• Preferred: Experience with real-time streaming data technologies like Kafka, Flink, or Pub/Sub
• Preferred: Bachelor's degree in Computer Science, Statistics, or a related field
• Familiarity with MLOps tools such as MLflow, Weights & Biases, etc.
  
  

Responsibilities

• Design, develop, and maintain scalable and reliable ML infrastructure for feature engineering, model training, prediction, and deployment
• Train, validate, and deploy high-performance ML models, applying advanced techniques in feature selection, hyperparameter tuning, and model architecture optimization
• Collaborate with data science teams to research, develop, and deploy new features that enhance model accuracy and performance
• Implement comprehensive model monitoring, automated training pipelines, and observability solutions to ensure ongoing model health and performance
• Optimize feature engineering pipelines for performance and scalability in a production environment
• Apply CI/CD principles to automate testing, validation, and deployment processes for ML models
• Work closely with cross-functional teams to understand product requirements and translate them into effective ML solutions
• Stay updated with the latest advancements in machine learning and AI to continuously improve our platform's capabilities
  
  

Benefits

• Competitive salary range of $120,000 - $190,000, commensurate with experience and location
• Equity options providing ownership in the company
• Comprehensive medical, dental, and vision coverage
• Life and disability insurance benefits
• 401(k) retirement plan with company matching
• Flexible time off policies to support work-life balance
• Paid parental leave for new parents
• Opportunities for professional growth and development in a fast-paced, innovative environment
  
  

Equal Opportunity

RADAR is committed to creating an inclusive and diverse workplace. We are an equal opportunity employer and do not discriminate based on race, ethnicity, gender, age, sexual orientation, gender identity or expression, disability, or any other protected status. We believe that diverse perspectives foster innovation and are essential to our success. All qualified applicants are encouraged to apply, and we welcome candidates from all backgrounds to join our team.