Field Application Engineer

Stealth AI Startup; El Segundo (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Stealth AI Startup in California seeks a Field Applications Engineer (FAE) / AI Solutions Architect to drive adoption of advanced AI hardware and software across edge devices. You will partner with customers, Sales, and Engineering to architect, deploy, and optimize AI solutions for computer vision, audio processing, and sensor fusion, leading PoCs and customer enablement.

The role requires hands-on technical leadership across hardware and software, plus the ability to communicate complex

Qualifications

• Bachelor's degree in a technical discipline required.
• Minimum 4 years in FAE, Solutions Architecture, or similar.
• Strong Python and ML framework experience (TensorFlow, PyTorch, ONNX).
• Experience deploying ML solutions for computer vision and related AI domains.

Responsibilities

• Partner with customers to understand requirements and architect AI solutions.
• Collaborate with Sales and Engineering to deliver hardware and software solutions.
• Serve as the technical advisor through the engagement lifecycle, from evaluation to deployment.
• Lead discovery sessions, PoCs, demonstrations, and customer enablement.
• Manage customer-facing technical projects ensuring successful integration and delivery.
• Diagnose and resolve complex software/hardware/system integration issues.

Skills

Python

Machine learning

TensorFlow

PyTorch

ONNX

Computer vision

Embedded systems

ASIC development

Git

Communication

Education

Bachelor's degree in Computer Science or related field

Tools

Git

Job description

Field Applications Engineer (FAE) / AI Solutions Architect

Join a cutting-edge semiconductor and artificial intelligence company developing next-generation edge AI technologies. This role offers the opportunity to work at the forefront of machine learning, embedded systems, and advanced computing, partnering with global customers to architect, deploy, and optimize innovative AI solutions. As a trusted technical advisor, the Field Applications Engineer (FAE) / AI Solutions Architect bridges the gap between customers, Sales, and Engineering, driving successful adoption of advanced AI hardware and software technologies.

Key Responsibilities

• Partner with customers to understand technical requirements and architect AI solutions tailored to application-specific needs.
• Collaborate with Sales and Engineering teams to develop, evaluate, and deliver customer-focused hardware and software solutions.
• Serve as the primary technical advisor throughout the customer engagement lifecycle, from initial evaluation through deployment and production support.
• Lead technical discovery sessions, proof-of-concept engagements, solution demonstrations, and customer enablement activities.
• Manage customer-facing technical projects, ensuring successful execution, integration, and delivery.
• Diagnose and resolve complex software, hardware, and system integration issues while coordinating with cross-functional engineering teams.
• Guide customers through installation, configuration, optimization, and deployment of AI technologies.
• Present complex technical concepts, system architectures, and implementation strategies to both technical and executive audiences.
• Support AI deployments across computer vision, audio processing, sensor fusion, and anomaly detection applications.
• Apply knowledge of ASIC development methodologies, including synthesis, place-and-route, and hardware implementation workflows, to support customer engagements and technical evaluations.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or a related technical discipline.
• Minimum of four years of experience in Field Applications Engineering, Solutions Architecture, Machine Learning Engineering, or a related technical role.
• Strong proficiency in Python and machine learning frameworks, including TensorFlow, PyTorch, and ONNX.
• Experience developing and deploying machine learning solutions for computer vision, including object detection, image classification, and facial recognition.
• Experience with audio AI applications, including keyword spotting, is desirable.
• Strong understanding of deep learning architectures, including CNNs, RNNs, Transformers, and State Space Models.
• Experience with Git version control and collaborative software development workflows.
• Working knowledge of AI hardware acceleration, embedded systems, CPUs, and ASIC development methodologies.
• Broad understanding of machine learning, deep learning, edge AI, and neuromorphic computing concepts.

Core Competencies

• Customer-facing technical leadership
• AI solution architecture and system design
• Technical project management
• Cross-functional collaborationTechnical presentations and customer enablement
• Analytical problem solving
• Excellent written and verbal communication skills
• Self-motivated with a strong commitment to continuous learning and professional development