Software Engineer (AI/ML/CV)

Summary In this role, you will take end-to-end ownership of converting complex problem statements into scalable, state-of-the-art machine learning solutions. Working at the intersection of data engineering, research, and deployment, you will harness LLMs, VLMs, and Transformer architectures to build, optimize, and version high-impact models alongside a collaborative team of ML engineers. Responsibilities Handle all aspects of data filtering and agglomeration. Collaborate with other ML Engineers to brainstorm on best practices, updates on SOTA models. Handle all translation of problem requirements to choice of architecture, codebase, and datasets. Enhancements of in-house/available open-source repositories to meet problem requirements. Work with data labeling teams to handle annotation metadata for your datasets. Handle all aspects of the Machine Learning cycle including data preprocessing, augmentations, training, model and experiment versioning, ablation studies and benchmarking. Qualifications Bachelors or Masters Degree in Computer Science or related disciplines. 2 - 4 years of experience required. At least 1 year of experience with LLMs/VLMs including their architecture, training, datasets, and knowledge of SOTA models and frameworks to leverage these models. Strong theoretical and prior experience of CNNs and Transformers including their usage in at least one successful product deployment Fluency in Python Programming. Working knowledge of C/C++ desirable. Familiarity with ML Frameworks like Pytorch, TensorFlow etc. Familiarity with MLOps, including Model Quantization, usage of annotation tools and model versioning tools like MLFlow. Strong background in Mathematics and Statistics. Sharp problem solving skills and ability to resolve ambiguous requirements Familiarity with Dockers.