Audio Machine Learning Jobs in Massachusetts (NOW HIRING)

Your Impact
We are seeking multiple highly skilled Full-Stack members of Technical Staff (MTS) to join our CoreAI organization, driving end-to-end development of AI systems across Cloud, Edge Devices, Mission Critical and Robotics platforms.
This role goes beyond pure research. You will operate across the full stack, from data, models, and infrastructure to system integration and production deployment, to deliver scalable, real-world AI solutions. You will work on cutting-edge applications spanning computer vision, NLU, multimodal AI (MLLMs), and GenAI, enabling intelligent perception, reasoning, and action in mission-critical environments.
As a senior technical leader, you will partner closely with research scientists, machine learning engineers, hardware, firmware, and product teams to translate advanced algorithms into robust, production-ready systems that operate reliably at scale.

You will have the opportunity to own and shape end-to-end AI systems that operate in real-world environments, bridging the gap between cutting-edge research and impactful production deployment. This role is ideal for engineers who thrive at the intersection of AI, systems, and product, and want to build scalable, high-impact solutions across cloud and edge.
What You'll Do
Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see https://www.axon.com/company)

• US: Seattle, Boston, Scottsdale

• Own end-to-end system development across data pipelines, model development, evaluation, and deployment for AI-powered products.
• Design and build scalable, production-grade systems for real-time perception, multimodal understanding, and decision-making.
• Develop and deploy models across cloud and edge environments, including resource-constrained devices.
• Architect and optimize full-stack AI pipelines, including:
• Translate research advances in computer vision, NLU, GenAI, and multimodal LLMs into production systems.
• Collaborate cross-functionally with MLE, hardware, firmware, and product teams to integrate AI into real-world systems.
• Optimize solutions for hardware-specific acceleration (GPU, NPU, DSP) and edge deployment.
• Define and drive evaluation frameworks and metrics to ensure system performance, reliability, and safety.
• Lead technical direction for complex, ambiguous problems and influence system architecture across teams.
• Contribute to technical design docs, internal knowledge sharing, and long-term platform strategy.

• Master's, or PhD in Computer Science, Electrical Engineering, or related field
• 8+ years (L8) or 10+ years (L9) of industry experience building production systems
• Strong programming skills in Python/C++ and experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
• Proven experience delivering end-to-end systems from concept to production
• Deep expertise in one or more areas:
• Experience building and scaling distributed systems or cloud-based ML pipelines
• Experience optimizing models for latency, cost, and deployment constraints

• Experience deploying AI both on Cloud (AWS, AzureML), edge devices (e.g., mobile, embedded systems, robotics platforms on Qualcomm, NVIDIA, Intel)
• Familiarity with hardware acceleration frameworks (TensorRT, ONNX, SNPE, etc.)
• Experience with real-time systems and streaming data pipelines
• Knowledge of multimodal data processing (vision, audio, text, sensor fusion)
• Experience with AWS or other cloud platforms for large-scale inference and training
• Strong system design and architecture skills across cloud edge environments
• Track record of technical leadership, mentoring, and driving cross-team initiatives
• Experience in privacy-preserving AI, security, or safety-critical systems

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, Dental, Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work

Location: This role is based out of our Boston, MA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesday through Friday, with flexibility to work remotely on Mondays. We believe connection fuels innovation, and our in-office culture is designed to support meaningful teamwork and mentorship.