Machine Learning Engineer

Must to have:
• Strong proficiency in Python, including NumPy, Pandas, Nvidia CUDA.

• Strong understanding of statistics, probability, linear algebra, & machine learning fundamentals.

• Hands-on experience building, training, evaluating, and optimizing machine learning models / or LLMs.

• Experience with data preprocessing, feature engineering, exploratory data analysis (EDA), and model evaluation.

• Ability to define evaluation metrics, conduct experiments, and interpret model performance.

• Familiarity with Git, APIs, and deploying models into production environments.

• Strong problem-solving skills and the ability to translate business requirements into data-driven solution.

Good to have:

• Familiarity with speech processing, ASR, TTS, or conversational AI.

• Familiarity with inferencing frameworks.

• Experience with LLMs, embeddings, vector databases, & RAG pipelines.

• Knowledge of audio analytics, real-time communication data, or voice AI applications.

 • Understanding of MLOps, model monitoring, and production model optimization.