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Strong Tier-1 brand, mid-level ML role, and generalist ML demand raise competition.
ML engineering skills transfer across industries but require domain-specific ML experience.
Explicit 5–7 years plus production ML and LLM requirements enforce strict technical filters.
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Design, build, deploy, and operate machine learning features and services with end-to-end ownership, including ML pipelines and model behavior monitoring in production.
Develop and own LLM-based features such as prompt strategies, evaluation pipelines, chatbots, or agent workflows using frameworks like LangChain, LlamaIndex, OpenAI SDK, etc.
Solve complex ML and system-level problems independently and participate in technical design discussions to influence implementation decisions.
5-7 years relevant work experience in machine learning or related fields.
Proficiency in at least one machine learning or deep learning framework.
Bachelor's Degree or equivalent combination of education and experience.
Strong foundations in data structures, algorithms, and statistics.
Experienced in building, deploying, and operating production ML systems with demonstrable end-to-end ownership.
Ability to translate ambiguous product requirements into concrete ML technical solutions and collaborate effectively across teams.
Comfortable with advanced LLM-based technologies and frameworks, showing strategic understanding of tradeoffs and implementation details.