Client : Product Based MNC

Location : Bangalore (Hybrid)

Designation : AI/ML (Data) Engineer

Exp : 7 to 14 yrs

Responsibilities :

- Develop, maintain, and optimize data pipelines and workflows and Feature Store to ensure seamless data ingestion and transformation as a scalable data solution.

- Design, develop, implement, and architect pipelines, considering performance & scalability including data storage and processing.

- Identification and redaction of organization and customer specific sensitive information using Gen AI and other NLP techniques as applicable.

- Using AI/ML techniques detection of anomalies in the data and unusual patterns.

- Text data extraction and summarization using LLM/SLM based applications and NLP techniques as applicable.

- Implementing and automation of observability solutions end to end for data pipelines.

- Using AI tools & agents in Databricks for efficient and effective data transformations and execution of pipelines.

- Building AI applications that can interact with MCP server(s) to extract required data from different sources and tools.

- Implement advanced data transformations and quality checks to ensure data accuracy, completeness, security and consistency of data.

- Seamlessly integrate data from diverse sources, for data ingestion, transformation and storage, leveraging AWS S3 Storage and possibly Snowflake as a SQL Data Warehouse.

- Create and implement advanced data models and schemas and ensure data governance and data management best practices.

Qualification and Desired Experiences :

- 7+ years of data analysis and AI/ML engineering experience.

- Bachelors degree in computer science, Statistics, Informatics, Information Systems or another quantitative field.

- Working knowledge of API or Stream-based data extraction processes like Salesforce API and Bulk API and have hands-on experience in web crawling.

Primary Tech skills :

- Advanced Web-crawling & scraping methods and tools.

- Building end-end pipelines for Semi and unstructured data (Text, all kinds of simple/complex table structures, images, video and audio data).

- Usage of AI/ML techniques, relevant libraries, ML models and algorithms.

- Working with Gen AI applications, LLMs, prompt engineering, embedding models.

- Working with vector databases, Text analytics, NLP techniques.

- Working with MCP servers, building AI applications.

- Python, Pyspark, SQL, RDBMS.

- Data Transformation (ETL/ELT) activities.

- SQL Data warehouse (e.g. Snowflake) working / preferably administration.

Secondary Tech skills :

- Databricks.

- Familiarity with AWS services : S3, Glue, EMR, EC2, RDS, monitoring and IAM.

- Kafka, Spark & Kafka Streaming.

- Workflow automation (e.g. using Github actions).

- Performing RCA.