Senior Software Engineer

Vaga não está no LinkedIn

🕒 Maio 22

🗽 New York – Remoto

🗽 New York – Remote

💵 $125.000 - $150.000 / ano

⏰ Tempo Integral

🟠 Sênior

🧑‍💻 Engenheiro Full-stack

Candidatar-se

Encontrar Vagas Remotas Similares

Receber Emails de Vagas Remotas

📊 Verifique sua pontuação de currículo para esta vaga

Melhore suas chances de conseguir uma entrevista verificando sua pontuação de currículo antes de se candidatar.

Enviar Currículo

Dotdash Meredith

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

Fundada em 2017

📱 Mídia

Media • Publishing

A Dotdash Meredith é a maior editora digital e impressa dos Estados Unidos, reconhecida por criar conteúdos confiáveis sobre uma ampla gama de tópicos, incluindo saúde, finanças, beleza e lar. Com o compromisso de fornecer as experiências que as pessoas desejam e as respostas de que precisam, a Dotdash Meredith alcança quase 200 milhões de pessoas a cada mês através de suas diversas marcas, como PEOPLE, Investopedia, Serious Eats e Byrdie. A empresa oferece ferramentas inovadoras, como a Ferramenta de Segmentação por Intenção, para aprimorar suas capacidades de publicidade digital. A Dotdash Meredith é reconhecida por sua profunda expertise em conteúdo editorial e publicação premium, tornando-se uma fonte confiável tanto para inspiração quanto para informações essenciais.

Descrição

• Design and build systems, manage scalable ML pipelines using Vertex AI Pipelines for training, evaluation and deployment • Develop and maintain data pipelines that support feature generation, model training, and analytics workflows • Own vector generation via Milvus, storage, and retrieval workflows • Implement model serving solutions using KServe and build APIs using FastAPI for low latency inference • Build observability and monitoring for models and pipelines. Track performance, drift, failures, and data quality issues • Collaborate with data scientists, product managers, and platform teams to define and deliver ML driven features • Investigate production issues across data pipelines, models, and services • Identify bottlenecks and improve reliability and performance • Create and maintain clear documentation for pipelines, models, APIs, and operational processes • Develop internal tools and dashboards to provide visibility into data processing and model behavior for stakeholders • Contribute to engineering standards, code quality, and best practices across Python-based services and ML systems • Stay current with ML infrastructure, MLOps practices, and relevant tools

🎯 Requisitos

• Bachelor’s degree in Computer Science, Engineering, or a related field • 6+ years of experience building scalable backend systems and services • 5+ years of experience developing software using object oriented languages, with strong proficiency in Python, Node.js, and TypeScript • Hands on experience with ES for search, indexing, and relevance tuning • Experience with event driven systems using Apache Kafka for real time data pipelines and processing • Strong understanding of version control systems including Git and platforms like Bitbucket • Experience with observability and monitoring tools such as Grafana, Kibana, and APM • Familiarity with cloud platforms including AWS and GCP, along with containerization using Docker and orchestration with Kubernetes • Comfortable deploying, versioning, and monitoring models in production • Curiosity to learn new technologies, especially in AI, LLMs, and modern search and recommendation systems • Experience designing and building data pipelines using Apache Beam and Apache Airflow for ingestion, transformation, and feature pipelines • Familiarity with experimentation and analytics tools such as Jupyter Notebook and Apache Spark to track and reproduce experiments • Strong experience designing and consuming RESTful and GraphQL APIs, including versioning, documentation, and security practices like OAuth and JWT • Good understanding of machine learning concepts including supervised learning, unsupervised learning, deep learning, and natural language processing, with practical application in ranking, retrieval, and personalization • Beginner level experience managing ML pipelines using Vertex AI Pipelines for training, evaluation, and deployment workflows • Ability to review code, provide clear feedback, and improve overall engineering quality • Strong communication skills. Able to explain technical concepts clearly to both technical and non technical stakeholders • Solid problem solving skills with a data driven approach

🏖️ Benefícios

• medical, dental, vision, prescription drug coverage • unlimited paid time off (PTO) • adoption or surrogate assistance • donation matching • tuition reimbursement • basic life insurance • basic accidental death & dismemberment • supplemental life insurance • supplemental accident insurance • commuter benefits • short term and long term disability • health savings and flexible spending accounts • family care benefits • a generous 401K savings plan with a company match program • 10-12 paid holidays annually • generous paid parental leave (birthing and non-birthing parents) • voluntary benefits such as pet insurance, accident, critical and hospital indemnity health insurance coverage, life and disability insurance