Digital Signal Processing (DSP) Engineer – AI/ML Ops
Location: Chicago, IL (Hybrid/Onsite Preferred)
Responsibilities
• Design and implement advanced DSP algorithms for real-time and offline signal processing.
• Develop AI/ML models for signal classification, anomaly detection, feature extraction, and predictive analytics.
• Build scalable data pipelines for signal acquisition, preprocessing, and model training.
• Deploy ML models into production using MLOps best practices.
• Optimize DSP and AI algorithms for latency, throughput, and computational efficiency.
• Collaborate with data scientists, embedded engineers, and software development teams.
• Implement CI/CD pipelines for machine learning workflows.
• Monitor production models for drift, performance, and reliability.
• Work with cloud-native AI services and containerized deployments.
• Document architecture, algorithms, and deployment processes.
Required Qualifications
• Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• 5+ years of experience in Digital Signal Processing.
• Strong knowledge of: o Digital Filters o FFT o Wavelets o Spectral Analysis o Adaptive Filtering o Time-Series Signal Processing
• Proficiency in Python and C/C++.
• Experience with TensorFlow or PyTorch.
• Hands-on experience building ML pipelines.
• Experience with Docker and Kubernetes.
• Experience with Git and CI/CD. Preferred Qualifications
• Experience with MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML.
• Experience deploying AI models at the edge.
• Familiarity with NVIDIA CUDA or GPU optimization.
• Experience with audio, radar, RF, image, LiDAR, or sensor signal processing.
• Knowledge of LLMs and Agentic AI is a plus.
• Experience working in regulated industries (Healthcare, Automotive, Aerospace, Telecom, Industrial).
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