Senior Machine Learning Engineer

Responsibilities:

1. Pipeline Development:

• Own end-to-end ML pipeline design, from edge device signal extraction to cloud-side inference systems.
• Build and evaluate scalable VLM workflows for generating labels and annotations.

2. Technical Collaboration:

• Collaborate with Embedded Systems and Hardware teams on device-side preprocessing and data-forwarding strategies.
• Work with Data Science to create evaluation frameworks for model accuracy and regression detection.

3. Innovation and Integration:

• Benchmark and integrate commercial and open-source Vision-Language Models.
• Stay current on advancements in vision-language capabilities and apply pragmatic engineering principles.

Qualifications:

• 5+ years in machine learning engineering with computer vision and/or LLM/VLM systems.
• Proficiency with modern ML stack: Python, PyTorch, cloud inference APIs, and experiment tracking.
• Strong familiarity with VLMs like GPT-4V, Claude, Gemini, or LLaVA and practical prompt engineering skills.
• Experience in building and evaluating labeling systems at scale and understanding edge device constraints.
• Pragmatic mindset for reliable production systems and ability to work independently in a fast-paced environment.