Dotdash Meredith

2 months ago

Senior Software Engineer 1, ML

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 15 hours agoStatus: Live

Job Summary

Own the design, development, and continuous improvement of the personalized recommendation engine powering the user’s product feed. Build multi-signal, embedding-based models using live retailer feeds, ingest data at scale, and collaborate with product, engineering, and data teams to deliver high-ownership personalization for millions of shoppers. Remote or hybrid with office days, contributing to a next-generation discovery platform.

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Seniority: Sr. Manager level

Key Responsibilities

•Design and build the core personalization engine using user-saved product data as behavioral signals and develop multi-signal recommendation models.
•Architect and maintain robust data ingestion pipelines to normalize and enrich product feeds from thousands of retail partners.
•Own the ranking and real-time assembly of each user’s personalized feed, balancing relevance, novelty, and business goals.
•Create clear documentation for pipelines, models, APIs, and system design; contribute to ML systems and scalable infrastructure best practices.
•Lead rigorous experimentation, including A/B and multivariate testing, and translate model results into product decisions.

Pay and Benefits

Salary: USD 160,000 - 180,000 annually

Perks:Health InsuranceDentalVision401kPaid LeaveRemote Work

Key Requirements

•5+ years of ML engineering experience focused on recommendation systems, personalization, or search ranking with hands-on depth in collaborative filtering, matrix factorization, content-based, and hybrid neural approaches.
•Proven experience designing, training, and deploying embedding models and vector retrieval (e.g., Milvus, Pinecone) for product or content similarity at catalog scale.
•Production experience serving real-time, low-latency ML predictions and managing the full model lifecycle — training, deployment, versioning, and monitoring — on cloud ML platforms such as AWS SageMaker or GCP Vertex AI (including Vertex AI Pipelines).
•Extensive backend engineering with strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, or JAX), plus working knowledge of Node.js and TypeScript.
•Core tech stack: Backend/API development using Python, FastAPI, Node.js, and TypeScript; Elasticsearch; Kafka; vector search with Milvus/Pinecone; cloud with AWS/GCP; Docker and Kubernetes; REST/GraphQL; OAuth/JWT; monitoring with Grafana/Kibana

Experience:5+ yearsRetailE-commerceMachine learning

Education:Bachelor's

Skills:CommunicationProblem-solvingCollaborationDocumentationResults-oriented

Languages:English

Tech Stack:PythonFastAPINode.jsTypeScriptElasticsearchApache KafkaMilvusPineconeAWS SageMakerGCP Vertex AIDockerKubernetesRESTGraphQLOAuthJWTSparkBeamAirflowFlink

Company Brief

Dotdash Meredith

Dotdash Meredith is a major digital and print media company producing lifestyle, entertainment, and news content across numerous brands and platforms, combining Dotdash's digital expertise with Meredith's legacy publishing portfolio following their 2021 merger.

Industry: Publishing

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Headquarters: New York, United States

Founded: 2021

Website LinkedIn

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Dotdash Meredith

2 months ago

Senior Software Engineer 1, ML

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 15 hours agoStatus: Live

Job Summary

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Seniority: Sr. Manager level

Key Responsibilities

•Design and build the core personalization engine using user-saved product data as behavioral signals and develop multi-signal recommendation models.
•Architect and maintain robust data ingestion pipelines to normalize and enrich product feeds from thousands of retail partners.
•Own the ranking and real-time assembly of each user’s personalized feed, balancing relevance, novelty, and business goals.
•Create clear documentation for pipelines, models, APIs, and system design; contribute to ML systems and scalable infrastructure best practices.
•Lead rigorous experimentation, including A/B and multivariate testing, and translate model results into product decisions.

Pay and Benefits

Salary: USD 160,000 - 180,000 annually

Perks:Health InsuranceDentalVision401kPaid LeaveRemote Work

Key Requirements

•5+ years of ML engineering experience focused on recommendation systems, personalization, or search ranking with hands-on depth in collaborative filtering, matrix factorization, content-based, and hybrid neural approaches.
•Proven experience designing, training, and deploying embedding models and vector retrieval (e.g., Milvus, Pinecone) for product or content similarity at catalog scale.
•Production experience serving real-time, low-latency ML predictions and managing the full model lifecycle — training, deployment, versioning, and monitoring — on cloud ML platforms such as AWS SageMaker or GCP Vertex AI (including Vertex AI Pipelines).
•Extensive backend engineering with strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, or JAX), plus working knowledge of Node.js and TypeScript.
•Core tech stack: Backend/API development using Python, FastAPI, Node.js, and TypeScript; Elasticsearch; Kafka; vector search with Milvus/Pinecone; cloud with AWS/GCP; Docker and Kubernetes; REST/GraphQL; OAuth/JWT; monitoring with Grafana/Kibana

Experience:5+ yearsRetailE-commerceMachine learning

Education:Bachelor's

Skills:CommunicationProblem-solvingCollaborationDocumentationResults-oriented

Languages:English

Tech Stack:PythonFastAPINode.jsTypeScriptElasticsearchApache KafkaMilvusPineconeAWS SageMakerGCP Vertex AIDockerKubernetesRESTGraphQLOAuthJWTSparkBeamAirflowFlink

Company Brief

Dotdash Meredith

Industry: Publishing

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Headquarters: New York, United States

Founded: 2021

Website LinkedIn