Match Score
Against your primary resumeLogin to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Protocol Intelligence
Data-driven signals on your job's competitivenessLog in to see why each signal reads the way it does.
Job Description
Structured overview of role & requirementsAbout This Role
Own end-to-end development of scalable machine learning solutions leveraging LLMs, VLMs, and Transformer architectures.
Manage all stages of the ML lifecycle: data preprocessing, augmentation, training, versioning, ablation studies, and benchmarking.
Collaborate with ML engineers and data labeling teams to translate problem requirements into architectures, codebases, and datasets.
Minimum Requirements
Bachelor's or Master's degree in Computer Science or related disciplines.
2-4 years of relevant experience, with at least 1 year working with LLMs/VLMs including architecture, training, and SOTA models.
Proficient in Python programming; working knowledge of C/C++ desirable.
Familiarity with ML frameworks (PyTorch, TensorFlow), MLOps tools (model quantization, annotation, MLFlow), and Docker.
Ideal Candidate Profile
Experienced with CNNs and Transformers validated by at least one successful product deployment.
Strong theoretical and practical grounding in ML, mathematics, and statistics enabling resolution of ambiguous requirements.
Comfortable working at the intersection of data engineering, research, and production with collaborative teams to innovate ML solutions.