Machine Learning Engineer

Required Skills & Experience: Hands-on code mindset with deep understanding in technologies / skillset and an ability to understand larger picture. Sound knowledge to understand Architectural Patterns, best practices and Non-Functional Requirements Overall, 8-10 years of experience in heavy volume data processing, data platform, data lake, big data, data warehouse, or equivalent. 5+ years of experience with strong proficiency in Python and Spark (must-have). 3+ years of hands-on experience in ETL workflows using Spark and Python. 4+ years of experience with large-scale data loads, feature extraction, and data processing pipelines in different modes - near real time, batch, realtime. Solid understanding of data quality, data accuracy concepts and practices. 3+ years of solid experience in building and deploying ML models in a production setup. Ability to quickly adapt and take care of data preprocessing, feature engineering, model engineering as needed. 3+ years of experience working with Python deep learning libraries like any or more than one of these - PyTorch, Tensorflow, Keras or equivalent. Prior experience working with LLMs, transformers. Must be able to work through all phases of the model development as needed. Experience integrating with various data stores, including: SQL/NoSQL databases In-memory stores

like

Redis Data lakes

(e.g., Delta Lake)

Experience with Kafka streams, producers & consumers. Required: Experience with

Databricks

or similar data lake / data platform. Required:

Java and Spring Boot

experience with respect to data processing - near real time, batch based. Familiarity with

notebook-based environments

such as

Jupyter Notebook

. Adaptability

: Must be open to learning new technologies and approaches. Initiative

: Ability to take ownership of tasks, learn independently, and innovate. With technology landscape changing rapidly, ability and willingness to learn new technologies as needed and produce results on job.

Preferred Skills

: Ability to pivot from conventional approaches and develop creative solutions.