Senior Software Engineer (NLP)
Published: 2025-11-08Consumer Edge (CE) is a preeminent data insight company targeting the global consumer. Since its founding in 2009 CE has focused on the nexus of data, research, and technology to fuel the discovery of consumer insights. We continue this focus today, delivering next generation data tools designed to answer complex questions on customer behavior. You are interested in joining CE ...
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Company overview
Consumer Edge is a data innovation and AI company transforming how professionals interpret consumer and business behavior. Our platform combines large-scale transaction data with advanced AI systems to deliver real-time insights to enterprise clients. Our technology team is distributed across Europe and North America, united by a focus on precision, scalability, and innovation.
Role summary
We are seeking an experienced Machine Learning Engineer with a specialization in Natural Language Processing (NLP) to solve one of our most critical and complex data challenges: entity resolution. In this role, you will design, build, and deploy production-scale systems to intelligently link records from disparate, massive datasets.
Your work will be foundational, creating a single, unified view of core entities (such as products, organizations, locations, and customers) that powers our analytics, product features, and business strategy. The ideal candidate is a hands-on problem-solver who thrives on end-to-end ownership—from collaborating on project scope and defining data needs to developing novel modeling strategies and deploying robust, scalable systems onto our cloud infrastructure (GCP & AWS).
Your main responsibilities
- Design & Build: Lead the end-to-end development of machine learning pipelines for large-scale entity resolution, record linkage, and data matching.
- NLP Modeling: Apply and customize advanced NLP techniques (e.g., entity extraction, semantic similarity, text vectorization, fuzzy matching) to compare and match entities from structured and unstructured text.
- System Architecture: Engineer scalable and efficient data processing and model inference systems designed to handle terabyte scale datasets using cloud-native tools.
- Deployment: Deploy, monitor, and maintain ML models and data pipelines in production on GCP (e.g., Vertex AI, BigQuery, Dataflow).
- Project Leadership: Collaborate closely with product managers, data engineers, and business stakeholders to scope new projects, define data requirements, and establish success metrics.
- Communication & Documentation: Create clear, comprehensive design documents and effectively communicate complex technical concepts, trade-offs, and results to both technical and non-technical audiences.
Required Experience
- 3+ years of hands-on experience building and deploying machine learning models in a production environment.
- Proven, demonstrable experience in Natural Language Processing (NLP) with a specific focus on entity resolution, record linkage, or data matching projects.
- Strong proficiency in Python and common ML/data science libraries (e.g., scikit-learn, pandas, spaCy, Hugging Face Transformers).
- Hands-on experience with ML deployment and data processing services on public cloud providers (GCP, AWS, or Azure).
- Solid software engineering fundamentals, including version control (Git), testing, and CI/CD practices.
- Excellent written and verbal communication skills, with a proven ability to document design decisions and present complex information clearly.
Desired experience
- Experience building data-intensive applications and working with very large datasets using distributed computing frameworks (e.g., Apache Beam, Apache Spark, Dask, Ray).
- Experience building NLP applications with an LLM based component
- Familiarity with MLOps principles and tools (e.g., MLflow, Kubeflow, TFX).
- Experience deploying AI/ML systems to production and integrating with data pipelines (e.g., ETL tools, Airflow, Dagster).
- Publications in relevant conferences (e.g., ACL, EMNLP, KDD) or contributions to open-source projects.
Tech stack & team context
You’ll work within the Basketview group, collaborating with AI Products and Location teams. Stack includes Python, FastAPI, BigQuery, Dataflow, and Vertex AI, with a strong emphasis on scalable NLP solutions. The team spans US and EU time zones and focuses on building practical, high-impact data intelligence systems.
Benefits & perks
We are a remote-first company with a distributed environment and flexible working arrangements. We believe that distributed workers should be first-class citizens. We also have an office in New York if offices are your thing.
Salary
The annual base salary for this role is between $175,000 – $225,000 based on experience, with the opportunity for a performance-based bonus, company equity, 401(k) matching, paid parental leave, flexible and generous time off, work-from-home flexibility, and subsidized health benefits.