Staff Research Engineer involved in creating a neurosymbolic AI agent at Onton. Focused on optimal decision - making processes and addressing challenges in current AI systems.
About the role
- Senior Software Engineer developing robust systems for perception and understanding in Computer Vision and Multimodal AI. Collaborating with teams to enhance product areas and build reliable workflows.
Responsibilities
- Design, build, and improve multi-stage computer vision pipelines that may include segmentation, detection, tracking, and VLM-based analysis, producing structured outputs (entities, attributes, actions/events, confidence, provenance)
- Build systems that handle real-world variability in visual inputs (for example: low resolution, poor lighting, motion blur, cluttered scenes, inconsistent capture devices)
- Work with diverse media types such as photos, video, timelapse, 360 video, and RGB-D when available
- Fuse visual evidence with contextual inputs such as metadata, documents, and sensor streams to improve recognition quality and reduce ambiguity
- Evaluate and integrate state-of-the-art vision and vision-language foundation models, including open-vocabulary recognition, grounded perception, segmentation, and multimodal reasoning
- Apply fine-tuning or adaptation approaches when needed; partner with ML teams on training, data strategy, and infrastructure best practices
- Define measurable acceptance criteria and benchmarking for accuracy, robustness, latency/cost, and reliability across datasets and domains
- Build scalable cloud workflows for batch processing and integrate outputs with APIs and downstream consumers
- Improve operational performance and cost via batching, caching, model selection, and pipeline observability
- Write maintainable code, contribute to design docs, code reviews, shared libraries, and cross-team technical decisions
Requirements
- Bachelor’s degree in Computer Science, Electrical Engineering, Robotics, or related field (or equivalent practical experience)
- 4+ years of experience building computer vision systems using Python
- Strong experience with deep learning for computer vision (detection, segmentation, and/or video understanding) using modern frameworks such as PyTorch
- Experience taking ML prototypes into reliable pipelines, including evaluation, monitoring, and failure analysis
- Experience building or integrating ML systems into cloud or backend workflows (batch processing and/or services)
- Strong collaboration and communication skills; ability to work across teams and stakeholders.
Benefits
- Annual cash bonuses
- Comprehensive benefits package
Job title
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