Website:
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Job details:
The AI Engineer will be responsible for developing proprietary machine-learning models that can interpret and reason through electrical and mechanical engineering work, enabling automated scoring and evaluation.
Responsibilities
- Design and build proprietary machine-learning models capable of reasoning about electrical and mechanical engineering work, including schematics, PCB layouts, CAD geometry, and related technical artifacts, for automated scoring and evaluation.
- Develop novel model architectures and training pipelines focused on technical reasoning, rather than just text generation, including multimodal reasoning across CAD/ECAD artifacts, simulation outputs, and candidate interaction traces.
- Convert real engineering tasks, such as circuit design, debugging, system integration, and mechanical design tradeoffs, into machine-interpretable representations that models can assess reliably and deterministically.
- Build and manage the full learning loop for these models, including data generation from assessment executions, trajectory capture, failure analysis, targeted dataset curation, “golden” supervision, continuous evaluation, and model iteration.
- Create scoring systems that are robust, defensible, and difficult to replicate, forming the technical foundation of the assessment platform.
Requirements
- Strong background in machine learning, including deep learning and modern foundation model architectures.
- Experience designing and operating end-to-end training and evaluation pipelines for production ML systems.
- Practical experience with retrieval-augmented generation systems and vector databases for large-scale knowledge and artifact retrieval.
- Experience working with noisy, real-world labeled datasets, including data cleaning, schema design, and quality control.
- Hands-on experience with reinforcement learning, including one or more of: reinforcement learning from human feedback, preference modeling and reward model training, or policy optimization for multi-step or tool-using agents.
- Experience building or training models on multimodal data, including text, images, video, or structured technical artifacts such as diagrams or CAD files.
Skills: machine learning,artificial intelligence,llm
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