Job Description
A leading financial services firm in Chandler, AZ is seeking a Senior Machine Learning Engineer to join their technology innovation team. In this position, you’ll be at the forefront of building state-of-the-art machine learning solutions, taking ownership of projects from the design phase through to on-device deployment.
You’ll architect and support robust pipelines for sensor data analysis, shaping ML systems that deliver real-time inference and anomaly detection on resource-constrained hardware. Collaborating closely with hardware, firmware, and platform teams, you’ll be responsible for seamlessly integrating and validating intelligent features within embedded environments. This role will involve building and automating MLOps solutions, overseeing experiment management, and ensuring scalable and compliant machine learning lifecycle practices suited to regulatory demands.

Key Responsibilities

• Lead the implementation of sensor data pipelines—from requirements through real-world integration
• Design, train, optimize, and deploy ML models specifically for edge or embedded platforms, focusing on performance and reliability
• Combine deep experience in Python with one or more frameworks (PyTorch, TensorFlow) to deliver production-ready models
• Partner with engineering and product teams to embed, monitor, and validate ML inference in device applications
• Develop infrastructure and automations for experiment tracking, continuous training, evaluation, and secure model deployment
• Maintain full documentation for all aspects of the ML lifecycle to enable audit, regulatory compliance, and operational excellence

Required Skills & Experience

• Extensive experience working with sensor and streaming data in production settings
• Expertise in Python and at least one major ML library (PyTorch, TensorFlow, or alternatives)
• Practical experience deploying models on edge systems (e.g., TensorRT, ONNX, TFLite, or similar technologies)
• Solid engineering background with proficiency in C or C++ for embedded systems collaboration
• Familiarity with MLOps and model versioning, preferably in a regulated environment

Preferred Qualifications

• 5+ years hands-on ML development, with significant experience in real-time or embedded applications
• Background working on medical, wearable, or robotics platforms highly desirable
• Demonstrated success working in cross-functional teams with hardware/firmware integration
• Experience in high-growth companies or small teams
• Bachelor’s or higher in Computer Science, Engineering, or a related field

Daily Activities

• This role is hands-on and project-focused, where you’ll design new ML workflows, transform raw data, and continually iterate on model performance
• You’ll support firmware engineers by ensuring seamless embedding and runtime validation of ML features
• Work with DevOps and MLOps teams to automate deployments and create scalable, reliable ML solutions
• Troubleshoot model issues, and refine algorithms for speed, accuracy, and compliance

Compensation & Benefits
Eligible for performance-based bonus or commission
Comprehensive benefits package including:

• Health, dental, and vision insurance
• Paid holidays and vacation
• 401(k) retirement plan with company match (if applicable)

Applicants must have current authorization to work in the US on a full-time basis, now and in the future