Senior ML & Automation Engineer

This is a fully remote position, open to applicants in India.

📋 Description

• Create and manage AI-driven pipelines that facilitate data acquisition, enhancement, and validation.

• Collaborate with Data Engineering and Operations teams to transition pipelines from prototype stages to full production.

• Design, develop, and assess machine learning models aimed at data enrichment and validation processes.

• Implement OCR, NLP, and layout recognition pipelines for effective data extraction.

• Develop microservices in Python for tasks such as document classification and metadata extraction.

• Integrate LLM APIs to enhance intelligent data extraction and task classification capabilities.

• Monitor, analyze, and optimize model performance metrics.

• Design and execute conversational AI solutions utilizing Amazon Connect and Amazon Lex.

• Create automated calling workflows to provide project updates from contractors.

• Ensure adherence to regulations regarding outbound communication practices.

• Work alongside Data Engineers to guarantee smooth integration of ML pipelines with data warehouses.

⛳️ Requirements

• Over 5 years of experience in machine learning, automation engineering, or a related field.

• Proficiency in Python, with practical experience using ML libraries such as scikit-learn, spaCy, TensorFlow, or PyTorch, along with production API integration.

• Demonstrable experience with OCR frameworks, including Tesseract, PaddleOCR, AWS Textract, or Google Document AI.

• Proven track record in implementing AWS Connect solutions, covering contact flow design, Amazon Lex bot development, and IVR configuration.

• Practical knowledge of LLM APIs (AWS Bedrock, OpenAI, Anthropic, or similar) for production extraction or classification tasks.

• Familiarity with document layout analysis tools like LayoutLM, Donut, DocTR, or equivalent.

• Strong understanding of entity extraction, NER, regex-based parsing, and rules-based methodologies.

• Experience in entity resolution, deduplication, or fuzzy record matching at scale.

• Solid grasp of data pipelines and ETL frameworks, with experience in deploying and monitoring ML models in live environments.

• Comprehensive knowledge of relational databases and SQL, as well as experience with large-scale data warehouses (e.g., Redshift, Snowflake, or similar).

• Understanding of outbound communication compliance (TCPA, Do Not Call regulations) in contexts involving automated or AI-driven calling.

• Exceptional problem-solving abilities, capable of translating operational business requirements into ML and automation solutions.

🏝️ Benefits

• Comprehensive health and wellness programs.

• Opportunities for professional development and continuous learning.

• Flexible working hours and remote work options.

• Collaborative and innovative work environment.

• Competitive salary and performance-based incentives.