ML Engineer
Algorized is a fast-growing deep-tech startup developing cutting-edge software for human positioning and sensing. By leveraging advanced algorithms, edge ML, radar, and sensor fusion, we enable precise people tracking, positioning, vital sign detection, and age classification.
We are seeking an ML Engineer to design, build, and maintain scalable machine learning infrastructure for deploying models that process data from sensors, radar, and cameras. This role will be critical in ensuring high performance, real-time accuracy, and seamless ML model operations. If you are resourceful, have deep understanding in system architecture, edge-computing, embedded systems and ready to join a dynamic fast-growing start-up this unique opportunity is for you!
LOCATION
Hybrid/Campbell California US
EMPLOYMENT TYPE
Full Time
Responsibilities
Qualifications
​​ML Engineering and Algorithms
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Design, improve and implement complex machine learning models and algorithms processing raw radar sensor data and other sensor data to address customer business needs
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Manage the machine learning pipeline, own the process of gathering, extracting, and compiling data across sources via relevant tools
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Format, re-structure, or validate data to ensure quality, and review the datasets to ensure it is ready for analysis
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Preprocess data for enhanced model accuracy and efficiency of people sensing and tracking
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Analyze extensive datasets to identify trends and patterns and interpret them
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Design tools for synthetic data generation and algorithm validation
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Test and develop new techniques to provide critical insights and communicate them clearly with stakeholders
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Build the foundation for highly scalable data collection and analytics
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ML Infrastructure & Model Deployment
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Design scalable ML pipelines to support sensor-agnostic (radar, camera) people-sensing model training, testing, deployment, and monitoring.
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Develop a scalable ML platform integrating ML pipelines and models, transforming raw sensor data into actionable people-sensing insights.
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Design ML workflows with CI/CD and robust model lifecycle management in mind.
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Implement monitoring tools (e.g., Prometheus, Grafana, Kibana) to track model accuracy, performance, and scaling issues.
Collaboration & Strategic Impact
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Cross-Functional Collaboration – Work closely with data scientists, software engineers, and product teams to define objectives, deliver key milestones, and align solutions with business needs.
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Technology Roadmap Contribution – Play a key role in shaping and executing Algorized’s AI-powered sensing platform roadmap.
Minimum Requirements
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MSc or advanced degree in a relevant field with 5+ years of experience in MLOps, ML model deployment, and cloud infrastructure.
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Experienced in Algorithm design and optimization
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Hands on experience in a similar position (Radar / LiDAR / Computer vision)
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Expertise in sensor fusion, edge AI, or embedded ML models for real-time applications.
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Knowledge of AI agent architectures or Reinforcement Learning concepts.
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Ability to collaborate efficiently with back-end systems.
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Familiar with APIs, WebSockets, GraphQL and databases.
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Experience with time-series data, sensor data pipelines, or stream processing frameworks.
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Good understanding of ML model deployment, CI/CD and monitoring frameworks
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Excellent teamwork & communication skills, with a passion for innovation and solving complex challenges.
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Willingness to travel domestically and internationally for development and on-site customer support.
Preferred Requirements
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Experience with Signal Processing and edge ML models.
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Familiarity with 3D positioning, tracking systems, or vital signs estimation.