Our Client Currently looking for Senior ML & Automation Engineer

Essential Functions :

Document Intelligence & Extraction :

– Design, develop, and evaluate machine learning models to automate data enrichment, classification, and validation across structured and unstructured project documents

– Implement OCR, NLP, and layout recognition pipelines to extract metadata, contacts, deadlines, and technical requirements from plan sets, specifications, and bid documents

– Build Python-based classification microservices to categorize documents by type and extract structured fields (e.g., bid dates, scope of work, discipline sheets, spec sections)

– Integrate LLM APIs (AWS Bedrock, Anthropic Claude, or equivalent) for intelligent extraction and classification tasks; optimize prompts and model calls for accuracy and cost efficiency

– Own model performance monitoring for one or more document domains tracking accuracy drift, false positives, and cost per-document over time

Conversational AI & AWS Connect :

– Design and implement conversational AI solutions using Amazon Connect and Amazon Lex, including contact flows, IVR design, and agent assist integrations for internal operational tooling

– Build and iterate on automated outbound AI calling workflows to collect project updates from contractors, subcontractors, and field contacts capturing structured responses and routing them into data pipelines

– Ensure all outbound communication automation is implemented in compliance with applicable regulations (TCPA, Do Not Call rules, B2B communication standards); partner with Legal and Compliance ahead of any production deployment

– Design conversation scripts with dynamic branching logic and fallback handling; continuously improve containment rates and data capture quality

– Monitor call performance, intent recognition accuracy, and fallback rates; iterate on Lex models and contact flows based on outcomes

Data Pipelines & Entity Resolution :

– Build pipelines that integrate scraped and API-sourced project data with external enrichment sources (ZoomInfo, LinkedIn, government open data APIs) to enrich company, contact, and project records

– Implement entity resolution and record deduplication logic including fuzzy name matching, license number anchoring, and cross-source reconciliation to maintain a clean entity master

– Develop automation scripts and microservices to reduce manual effort in project matching, contact discovery, and quality checks

– Collaborate with Data Engineers to ensure ML pipelines integrate seamlessly with existing data warehouses (Redshift) and meet latency and cost targets

– Partner with data specialists to design feedback loops that validate and continuously improve model outputs

Education Requirement : Bachelor’s degree in a related field or equivalent education and work experience.

Required Experience, Knowledge And Skills :

– 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

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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