Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; a Master’s degree is preferred.
8+ years of experience in building AI models with ML, NLP and deep learning.
Proven track record of successfully delivering machine learning projects from concept to production.
Strong leadership, interpersonal skills, and ability to effectively communicate technical concepts to non-technical stakeholders.
Excellent problem-solving abilities and attention to detail.
Strong knowledge of AI/ML techniques, algorithms, and frameworks. Experience building and deploying ML models (classification, NLP, forecasting).
Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Strong programming skills in Python, and familiarity with libraries such as PyTorch, TensorFlow, and Scikit-Learn.
Exposure to Matplotlib, Seaborn, or Plotly
Solid understanding of machine learning concepts, algorithms, and statistical methods.
Experience with computer vision libraries (OpenCV, etc.) and NLP libraries (spaCy, Hugging Face, etc.).
Knowledge of MLOps practices and experience with CI/CD tools.
Good understanding of using LLMs via APIs or fine-tuning open-source models.
Hands-on with data prep (Pandas, Spark), feature engineering, model training and tuning.
Knowledge of vector stores, embeddings, and LLMOps tools (LangChain, LlamaIndex, etc.).
Experience with at least one cloud platform and CI/CD for ML (GitHub Actions, MLflow, etc.).
Exposure to monitoring frameworks (evidently.ai, whylogs, or custom dashboards).
Proven ability to work independently and with a team.
Extensive expertise in refining LLMs, implementing RAG architectures, Weaviate vector databases, and advanced prompt engineering.
