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Tier-1 brand, mid-level ML role, metro locations, and broad skill requirements increase candidate competition.
ML/LLM engineering skills transfer across industries, but domain-specific compliance or finance knowledge moderately matters.
Mandatory ML/LLM systems experience and specific tech stack (Python, Spark, TensorFlow, LLMs) imply strict screening.
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Contribute to design, development, and implementation of application systems with a focus on scalable and reliable machine learning systems including training, inference, monitoring, and iteration.
Analyze and resolve application issues, identify vulnerabilities and security concerns, and perform testing and debugging.
Serve as a subject matter expert (SME) advising senior stakeholders and supporting lower level analysts with autonomy and limited supervision.
Bachelor’s degree or equivalent experience in a relevant field.
Experience required in designing and developing machine learning/deep learning/LLM systems and proficiency with Python, SQL, Spark, PySpark, TensorFlow or similar programming environments.
Work Experience Required: Not explicitly mentioned in the JD.
Ability to work independently with limited supervision and exercise independent judgment.
Experienced in ML/DL/LLM algorithms, model architectures, and training techniques with hands-on programming expertise in Python and related analytical tools.
Comfortable working both independently and collaboratively within teams in a technology-driven application development environment.
Familiarity with distributed data/computing frameworks such as Hadoop, Hive, Spark, and databases like MySQL is a plus.