Back
Tier-1 brand, popular ML role, mid-level experience band, and Bengaluru metro location increase applicant competition.
Core ML engineering skills are transferable across industries, though product/networking domain knowledge moderately matters.
Explicit 4-9 years, deep learning and production ML requirements, and strong technical stack raise filter strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead design and architecture of AI and machine learning solutions for complex business problems ensuring scalability, performance, and maintainability.
Conduct advanced AI research, integrate emerging technologies, and develop production-level ML algorithms and models including deep learning.
Provide technical guidance, mentorship, and collaborate across teams to drive AI innovation and translate customer requirements into solutions.
Bachelor's degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline (Master’s desirable).
Typically 4-9 years of relevant experience in AI/ML engineering or research.
Proficiency in programming languages such as Python, R or Java, with experience in ML frameworks (e.g., TensorFlow, PyTorch) and software engineering best practices.
Willingness to work primarily onsite from an HPE office (Onsite requirement).
Experienced in developing advanced ML models including deep learning architectures (CNNs, RNNs, transformers) and performing model optimization and evaluation.
Capable of providing technical leadership and mentoring junior engineers, with strong communication skills to interact with cross-functional stakeholders.
Comfortable leading research initiatives and integrating state-of-the-art AI/ML techniques into scalable production systems within a complex enterprise environment.