Consumer Edge
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.
Remote‑first & benefits 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.
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.
Equal Employment Opportunity statement As set forth in Consumer Edge’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
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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.
Remote‑first & benefits 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.
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.
Equal Employment Opportunity statement As set forth in Consumer Edge’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
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