AI/ML Engineer (Computer Vision)

• →Design and deploy visual AI systems that turn complex technical drawings into structured, production ready data.
• →Build and improve model pipelines across training, evaluation, inference, and monitoring.
• →Partner with software engineers and product leaders to embed computer vision capabilities into customer facing workflows.
• →Improve latency, stability, and cost efficiency for image understanding workloads running in production.
• →Investigate model failures in live environments and convert findings into measurable performance gains.
• →Contribute to data strategy, experiment design, and repeatable evaluation methods.
• →Support scalable deployment practices across cloud infrastructure and ML operations workflows.
• →Help create a strong engineering culture built on curiosity, accountability, and practical execution.

• Strong hands-on experience with Python and modern deep learning frameworks.
• Background building or productionizing computer vision systems for document, image, or spatial understanding problems.
• Experience deploying AI or ML solutions into production environments.
• Comfort with cloud-based ML infrastructure and automated training or deployment workflows.
• Familiarity with inference acceleration tools such as ONNX, TensorRT, CUDA, or related optimization stacks.
• Ability to work independently, debug effectively, and move quickly in a build-oriented environment.

• Experience with object detection, segmentation, or 3D perception.
• Exposure to multimodal or visual language model approaches.
• Experience with edge deployment or performance sensitive inference.
• Prior work in startup or other fast-moving product environments.

You will have the chance to work on meaningful technical problems, influence product direction, and see your work move from concept to production quickly. This is a strong fit for someone who enjoys applied AI, values ownership, and wants direct visibility into the business impact of their work.

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