Role Overview
411 Locals is seeking an experienced AI/ML Engineer with specialized expertise in the Databricks Data Intelligence Platform. As we scale our operations, we are looking for a technical leader to bridge the gap between complex data infrastructure and practical business application.
In this role, you will architect and deploy scalable machine learning pipelines that drive intelligence across our two most critical data sources: Digital Marketing Performance and Call Center Operations. You will turn large volumes of SEO data and client interactions into actionable insights, automated agent assistance, and predictive models.
Key Responsibilities
1. Databricks Architecture & Data Engineering
- Lakehouse Architecture: Design, build, and maintain a robust Lakehouse architecture on Databricks (using Delta Lake) to unify structured marketing data and unstructured call center logs.
- Pipeline Development: Develop production-grade ETL/ELT pipelines using Apache Spark (PySpark) to ingest and normalize data from diverse sources, including CRM systems, Google Analytics, and telephony providers.
- MLOps & Governance: Implement end-to-end MLOps lifecycles using MLflow and Databricks Unity Catalog to ensure model governance, versioning, and seamless deployment to production.
2. AI for Call Center Optimization
- NLP & Speech Analytics: Deploy Large Language Models (LLMs) and NLP pipelines to transcribe, diarize, and analyze agent-client voice interactions at scale.
- Sentiment & Quality Assurance: Build models to detect customer sentiment and churn risk in real-time, automating Quality Assurance processes.
- Agent Assist Systems: Develop RAG (Retrieval-Augmented Generation) applications that provide live “next-best-action” recommendations to sales and support agents based on historical success data.
3. Marketing & Business Analytics
- Predictive Modeling: Create models to forecast client retention (churn prediction) and calculate Customer Lifetime Value (CLV) to optimize marketing spend.
- Attribution Modeling: Use advanced statistical modeling to determine the ROI of various marketing channels and digital marketing strategies.
- Process Automation: Utilize Generative AI to assist in automating performance reporting and content analysis.
Qualifications
Technical Expertise:
- Databricks: Extensive hands-on experience with the Databricks platform, including Workflows, Delta Live Tables, and Model Serving.
- Machine Learning: Strong proficiency in Python and standard ML libraries (TensorFlow, PyTorch, Scikit-learn). Experience deploying LLMs (Llama, OpenAI, or similar) within an enterprise environment.
- Big Data: Deep understanding of distributed computing, Apache Spark optimization, and SQL.
- Cloud Infrastructure: Experience with major cloud providers (AWS or Azure) and containerization (Docker/Kubernetes).
Domain Experience:
- Call Center Technology: Experience working with Telephony APIs or analyzing conversational data (Speech-to-Text/NLP).
- Digital Marketing: Familiarity with digital marketing KPIs (CPC, CTR, Conversion Rate) and SEO principles is highly desirable.
Core Competencies:
- Problem Solving: Ability to take ownership of a problem from concept to deployment.
- Communication: Ability to explain complex technical concepts and model predictions to non-technical stakeholders in Sales and Operations.
Preferred Skills
- Experience with dbt (data build tool) for data transformation.
- Background in working with legacy web systems or CRMs.
- Databricks Certification (Data Engineer or ML Practitioner).
- Professional development opportunities within a growing technology team.