Machine Learning Engineer

Senior Machine Learning Engineer

Confidential Search | Advanced AI Hardware Company

A publicly traded AI hardware company is seeking a Senior Machine Learning Engineer to develop and deploy state-of-the-art machine learning models optimized for next-generation low-power AI acceleration platforms.

This is a hands-on research and delivery role.

We're looking for someone who enjoys building as much as innovating. You'll develop novel model architectures, write production-quality Python and PyTorch code, and work closely with hardware and compiler teams to ensure models run efficiently on specialized AI silicon. Success in this role requires both technical depth and the ability to translate research into deployable solutions.

What You'll Work On

• Design, train, and optimize state-of-the-art machine learning models for low-power inference environments
• Develop architectures spanning State Space Models (SSMs), Transformers, hybrid sequence models, and machine learning approaches to signal processing challenges
• Collaborate closely with hardware and compiler teams to align model architecture, quantization strategies, memory utilization, and runtime efficiency
• Optimize models through quantization, pruning, distillation, sparsity techniques, and operator-level tuning
• Evaluate emerging application areas where specialized AI hardware can deliver meaningful advantages
• Translate research findings into product direction and technical strategy
• Stay current with advances in machine learning research and identify opportunities relevant to future product development
• Present technical findings internally and externally to customers, partners, and industry stakeholders
• Contribute to patents, publications, technical proposals, and strategic research initiatives

Technical Areas of Interest

• Deep learning and modern neural network architectures
• State Space Models (S4, Mamba, and related sequence modeling approaches)
• Transformer architectures and efficient inference techniques
• Signal processing fundamentals, including filtering, spectral analysis, stochastic processes, and time-series modeling
• Hardware-aware machine learning optimization
• Model compression and deployment techniques

Experience We Value

• Radar or sensor signal processing
• Large language models and generative AI
• Biomedical signal classification
• Audio and speech processing
• Vision-language models
• Agentic AI systems and Retrieval-Augmented Generation (RAG)
• Robotics and autonomous systems
• Model distillation and compression
• Embedded AI and edge deployment

Qualifications

• PhD Or Masters in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a related discipline
• Strong proficiency in Python and PyTorch
• Demonstrated ability to deliver machine learning solutions from concept through deployment
• Experience collaborating across machine learning, hardware, software, and business teams
• Strong written and verbal communication skills

Preferred

• Publications in leading conferences or journals
• Patent contributions
• Experience deploying models to AI accelerators, NPUs, DSPs, FPGAs, or other specialized compute platforms
• Experience with quantization-aware training, model compression, and efficient inference toolchains

This is an opportunity to join a small, highly technical team working at the intersection of machine learning, hardware acceleration, and edge AI. The role offers significant visibility, ownership, and the opportunity to influence both research direction and product strategy.