Design and operate AI-powered pipelines that transform data acquisition, enrichment, and validation.
Partner with Data Engineering and Operations to move pipelines from prototype to production.
Design, develop, and evaluate machine learning models for data enrichment and validation.
Implement OCR, NLP, and layout recognition pipelines for data extraction.
Build Python-based microservices for document classification and metadata extraction.
Integrate LLM APIs for intelligent extraction and task classification.
Monitor and optimize model performance tracking.
Design and implement conversational AI solutions with Amazon Connect and Amazon Lex.
Build automated calling workflows for project updates from contractors.
Ensure compliance with regulations for outbound communications.
Collaborate with Data Engineers to ensure seamless ML pipeline integration with data warehouses.

5+ years of experience in machine learning, automation engineering, or a closely related discipline
Proficiency in Python with hands-on experience using ML libraries (scikit-learn, spaCy, TensorFlow, or PyTorch) and production API integration
Hands-on experience with OCR frameworks — Tesseract, PaddleOCR, AWS Textract, or Google Document AI
Demonstrated experience implementing AWS Connect solutions — including contact flow design, Amazon Lex bot development, and IVR configuration
Practical knowledge of LLM APIs (AWS Bedrock, OpenAI, Anthropic, or equivalent) for production extraction or classification workloads
Familiarity with document layout analysis tools (LayoutLM, Donut, DocTR, or similar)
Strong knowledge of entity extraction, NER, regex-based parsing, and rules-based approaches
Experience with entity resolution, deduplication, or fuzzy record matching at scale
Strong knowledge of data pipelines and ETL frameworks; experience deploying and monitoring ML models in production
Solid understanding of relational databases and SQL; experience with large-scale warehouses (Redshift, Snowflake, or similar)
Awareness of outbound communication compliance (TCPA, Do Not Call regulations) in automated or AI-driven calling contexts
Strong problem-solving skills with the ability to translate operational business needs into ML and automation solutions.

Senior ML & Automation Engineer

Key skills