AI/ML Engineer

Job Title- AI/ML Engineer (Data Engineer) Exp- 7-14 yrs Location- Bangalore (Hybrid)

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
• Bachelor’s 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. 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