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Tier-1 employer plus a generalist early-career ML role increases applicant density.
Core ML and Python skills are broadly transferable across industries with minimal domain constraints.
Explicit 0–3 years requirement and general tech stack make shortlisting fairly permissive.
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Build and maintain machine learning and Generative AI pipelines including data preprocessing, training, evaluation, and inference.
Develop and support simple Retrieval-Augmented Generation (RAG) and NLP workflows, and integrate AI models into applications via backend APIs.
Collaborate with senior engineers and cross-functional teams to optimize models, ensure performance, and support deployment activities.
Bachelor’s degree in computer science, IT, or related field.
0–3 years of experience or strong academic/project background in AI/ML.
Proficient in Python programming with knowledge of ML libraries such as NumPy, Pandas, scikit-learn, or PyTorch/TensorFlow.
Basic understanding of ML concepts, NLP, model evaluation, APIs, and backend development.
Comfortable working with ML pipelines and basic Generative AI workflows under guidance, indicating a junior-level engineer fit for collaborative, supportive environments.
Experience or familiarity with backend development and API integration, showing ability to link ML models with software applications.
Adaptable and open to learning new AI/ML advancements in a fast-paced technology setting.