Dodge Construction Network

Dodge Construction Network combines five trusted brands to provide timely and accurate construction information, empowering businesses to find new jobs, make bids, and optimize sales strategies for growth.

Construction & Engineering

Industrials

251-1K (450)

Founded 2021

12 open positions

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Senior ML & Automation Engineer

2 weeks, 6 days ago

India

Full-time

Senior

SDET (Software Development Engineer in Test)

Quality Assurance and Testing

Agile AWS Confluence Docker Git JIRA Kubernetes Machine Learning Microservices MLflow NLP Python PyTorch SageMaker Scikit-learn Snowflake spaCy SQL TensorFlow

Apply Now

Dodge Construction Network

Construction & Engineering

251-1K

Founded 2021

View All Jobs 12

Description

Design, develop, and evaluate machine learning models for data enrichment, classification, and validation of structured and unstructured project documents.
Implement OCR, NLP, and layout recognition pipelines to extract metadata, contacts, deadlines, and technical requirements from construction documents.
Build Python-based classification microservices to categorize documents and extract structured fields.
Integrate LLM APIs for extraction and classification tasks while optimizing prompts and model usage for accuracy and cost.
Own model performance monitoring for document domains, including accuracy drift, false positives, and cost per document.
Design and implement conversational AI solutions using Amazon Connect and Amazon Lex, including contact flows, IVR design, and agent assist integrations.
Build automated outbound AI calling workflows to collect project updates and route structured responses into data pipelines.
Ensure outbound communication automation complies with TCPA, Do Not Call rules, and B2B communication standards.
Build pipelines that combine scraped, API-sourced, and externally enriched project data to improve company, contact, and project records.
Implement entity resolution and deduplication logic to maintain a clean entity master and reduce manual matching work.
Collaborate with Data Engineering, Operations, Legal, Compliance, and data specialists to move ML pipelines into production and improve them continuously.

Requirements

Bachelor’s degree in a related field or equivalent education and work experience.
5+ years of experience in machine learning, automation engineering, or a closely related discipline.
Proficiency in Python with hands-on experience using ML libraries such as scikit-learn, spaCy, TensorFlow, or PyTorch.
Hands-on experience with OCR frameworks such as 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 such as AWS Bedrock, OpenAI, Anthropic, or equivalent for production workloads.
Familiarity with document layout analysis tools such as LayoutLM, Donut, or DocTR.
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, plus experience deploying and monitoring ML models in production.
Solid understanding of relational databases and SQL, with experience in large-scale warehouses such as Redshift or Snowflake.
Awareness of outbound communication compliance requirements such as TCPA and Do Not Call regulations.
Experience with outbound AI calling automation, government and open data APIs, AWS analytics and ML services, inference cost optimization, CI/CD and MLOps tooling, sales intelligence/contact enrichment data, or Agile tools such as Jira and Confluence are preferred.

Interested in this position?

Apply directly on the company website

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