Meredith

Meredith

Senior Software Engineer 1, ML

Remote US · Senior

Sponsorship not specified$170k-$195kDetected 30 days ago
PythonNode.jsFastAPIGitElasticsearchVector DatabasesAWSGCPCloud PlatformsDockerKubernetesGrafanaAPI DevelopmentGraphQLRESTKafkaOAuthMachine LearningTensorFlowPyTorchSparkAirflowData EngineeringNLP

About the role

  • Users save, organize, and share products they're excited about - and our platform turns those signals into a deeply personalized shopping experience.
  • We ingest live product feeds from thousands of retailers and use a rich understanding of each user's taste to surface the right product at the right moment.

Responsibilities

  • As a Senior Software Engineer for personalization, you will own the design, development, and continuous improvement of the recommendation algorithm that powers the user's personalized product feed.
  • You'll work with a rich dataset of user-saved products and a live ingestion pipeline pulling from thousands of retailer feeds to build a system that learns each user's unique preferences across brand, category, color, price point, and fit.
  • You will collaborate closely with product, engineering, and data teams to define what great personalization looks like - and then build it.
  • Design and build the core personalization engine using user-saved product data as behavioral signals.
  • Develop multi-signal recommendation models that incorporate brand affinity, product category, color palette, fit/sizing signals, price sensitivity, and trends.
  • Build and maintain product embedding models that capture rich semantic similarity across the retailer feed catalog.
  • Develop cold-start strategies to generate high-quality recommendations for new users with limited save history.
  • Design and maintain robust pipelines to ingest, normalize, and enrich product feeds from thousands of retail partners.
  • Collaborate on a unified product taxonomy and attribute extraction layer that standardizes inconsistent retailer data into coherent features (category, color, material, fit, etc.).
  • Build and own the ranking and re-ranking layer that assembles each user's personalized feed in real time.

Requirements

  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • You have a strong foundation in modern backend and ML engineering practices and continue to learn and evolve.
  • Proven experience designing, training, and deploying embedding models and vector retrieval (e.g., Milvus, Pinecone) for product or content similarity at catalog scale.

Nice to have

  • Extensive backend engineering with strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, or JAX), plus working knowledge of Node.js and TypeScript.

Skills

  • Backend and API development using Python, FastAPI, Node.js, and TypeScript.
  • Search and indexing using Elasticsearch for relevance, retrieval, and query optimization.
  • Event driven architecture and streaming using Apache Kafka.
  • Vector search and embeddings infrastructure using vector databases such as Milvus or Pinecone.
  • Specific Knowledge, Skills, Certifications and Abilities:

Compensation

  • New York: $170,000 - $195,000 Remote US: $160,000 - $180,000
  • The pay range above represents the anticipated low and high end of the pay range for this position and may change in the future.
  • Actual pay may vary and may be above or below the range based on various factors including but not limited to work location, experience, and performance.
  • The range listed is just one component of People Inc's total compensation package for employees.
  • Other compensation may include annual bonuses, and short- and long-term incentives.

Benefits

  • Leverage NLP and computer vision techniques to extract attributes from unstructured product descriptions and images.
  • Partner with the data engineering team to maintain data quality, freshness, and catalog coverage at scale.

Company info

  • Our next-generation product discovery platform connects shoppers with the things they love across thousands of retail partners.
  • We're building the recommendation engine at the heart of this shopping experience - a system that understands not just what people save, but why they save it.
  • This is a foundational hire that will shape how millions of users discover products they love.
  • About The Positions Contributions:
  • Accountabilities, Actions and Expected Measurable Results
  • Recommendation Algorithm Development 30%
  • Implement and evaluate a range of approaches including collaborative filtering, content-based filtering, and hybrid neural architectures.
  • Data Ingestion & Feature Engineering 25%
  • Personalized Feed & Ranking 25%
  • Build A/B testing solutions to rigorously evaluate ranking and recommendation changes against key engagement metrics.
  • Engineering Excellence 20%
  • Own production systems. Debug issues across indexing, retrieval, ranking, and serving layers
  • Create clear documentation for pipelines, models, APIs, and system design.
  • Contribute to best practices for ML systems, API design, and scalable infrastructure.
  • Stay current with advancements in recommendation, ranking, and personalization systems and apply them where they make practical impact.

Visa & Work Authorization

  • to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender id
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