Back
Well-known firm, popular Data Scientist title, and mid-level (3+ years) experience increase competition.
ML/LLM skills are transferable across industries but GenAI specialization gives moderate domain preference.
Explicit 3+ years applied ML requirement plus specific LLM, PyTorch, and cloud skills raise filtering strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop, implement, and fine-tune generative AI and large language model experiments and workflows using Python and ML frameworks.
Support benchmarking, performance analysis, and anomaly detection of LLMs to improve the GenAI platform.
Contribute to data curation, preprocessing, documentation, and participate in model review sessions to apply state-of-the-art evaluation methods.
Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or related technical field.
0–7 years overall IT experience with 3+ years in applied machine learning or data science, including internships or academic research.
Proficiency in Python and experience with ML frameworks such as PyTorch or TensorFlow.
Familiarity with LLM architectures, fine-tuning techniques, evaluation metrics, and cloud AI/ML services (AWS, Azure, or GCP).
Early-career professional focused on experimental research and applied development with LLMs and generative models.
Comfortable working on-premise within a collaborative team involving senior data scientists and AI researchers.
Experienced in Python-based model training pipelines and familiar with MLOps practices for continuous model evaluation and improvement.