Description:
As a Senior Machine Learning Engineer within the AI Squad and reporting to the Director of AI Engineering, you'll contribute to the development of cutting-edge AI solutions to combat vehicle and content theft. In this senior role, you'll play a pivotal part in shaping our AI roadmap, mentoring junior engineers, and influencing system architecture decisions. This is a high-impact role with visibility across engineering and product leadership.
Responsibilities:
- Contribute to the design, development, and deployment of robust machine learning models for production use in real-world security applications.
- Develop within the full machine learning lifecycle; from problem definition to data pipeline design, model development, validation, deployment, and monitoring.
- Establish and refine best practices in our ML system architecture, CI/CD pipelines for ML, and reproducible research methodologies.
- Collaborate with cross-functional stakeholders including product managers, data engineers, and MLOps teams to ensure seamless model integration and delivery.
- Perform advanced exploratory data analysis on large-scale sensory datasets (image, audio, radar, accelerometer) to derive insights and guide modeling strategies.
- Stay ahead of industry advancements in machine learning, AI sensing, and signal processing, incorporating the latest innovations into technology stack.
- Mentor and guide junior engineers and contribute to the hiring process and technical reviews.
Requirements:
- 5+ years of professional experience developing and implementing ML for perception systems with expertise in at least one of either RADAR, camera, or LiDAR.
- Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
- Expertise in Python with extensive experience in at least one deep learning framework (PyTorch or TensorFlow.
- Proven ability to develop production-grade ML applications for training, evaluation and inference on large-scale datasets.
- Experience creating C/C++ applications utilizing modern language features and build systems, preferably for porting ML inference applications from Python to edge devices/embedded systems.
- White-box understanding of classical ML algorithms (SVMs, HMMs, Decision Trees) and modern neural network models and architectures (CNNs, transformers) with significant experience applying them for perception systems.
- Experience implementing and applying dynamic object tracking, with experience using sensor fusion as a preference.
- Proficiency in Unix-based environments (Linux, macOS) including working with remote servers and services, virtual computers and clusters.
- Proficiency in signal processing techniques such as time/frequency-domain processing (e.g. Fourier Transform), filtering, and noise reduction.
Preferred Qualifications:
- Experience in deploying models to edge hardware, including experience with PyTorch and ONNX and model compression techniques, e.g. quantization and pruning.
- Experience using cloud computing platforms, e.g., AWS or GCP.
- Experience with MATLAB for algorithm prototyping and research.
- Experience with Docker or containerization.
- Reside within the Detroit area or nearby, with the ability to work in a hybrid environment and regularly commute to our Detroit office as needed.
- Must be authorized to work in the US without sponsorship, now or in the future.
Benefits:
- Comprehensive medical benefits coverage, dental plans and vision coverage.
- Health care and dependent care spending accounts.
- Employee and Family Assistance Program (EAP).
- Employee discount programs.
- Retirement plan with a generous company match.
- Generous Paid Time Off, Sick, and Holidays
- Family Leave (Maternity, Paternity)
- Short- and long-term disability
- Life insurance and accidental death & dismemberment insurance
