Minimum Qualifications:

• Bachelor's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 3+ years of Hardware Engineering or related work experience.
OR
Master's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 2+ years of Hardware Engineering or related work experience.
OR
PhD in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 1+ year of Hardware Engineering or related work experience.

Core Technical Expertise:

    Strong software development experience (software engineering principles, algorithms, and data structures) with proficiency in Python.

    Strong foundations in mathematics for ML and ML Algorithms (regression, tree ensembles, SVMs, clustering, time series), feature selection (PCA, mutual information), and model interpretability.

    Hands-on experience with deep learning architectures (CNNs, RNNs, LSTMs, Transformers), training optimization (regularization, gradient clipping, learning rate scheduling), and advanced loss functions (contrastive, triplet).

    Ability to break down design requirements and propose innovative, scalable solutions.

o Additional Expertise

    Exposure to generative AI & LLMs: Experience with prompt engineering, RAG, parameter-efficient finetuning, context management, and LLM evaluation frameworks.

    Good understanding of VLSI Design Execution - with development experience on PnR or Synthesis or STA

    Tooling & Infrastructure: Proficient in Python, PyTorch/TensorFlow, Scikit-learn, Pandas, NumPy

6+ years experience