Machine Learning Engineer at AlphaSense

| Greater NYC Area
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About AlphaSense

AlphaSense provides an AI-based search engine for market intelligence, used by the largest and fastest-growing firms globally. Our mission is to curate and semantically index the world’s market and company information, including the vast high-value content sets that traditional web search engines cannot reach. With 1000+ enterprise clients, AlphaSense helps knowledge professionals become dramatically more productive, and gain an information edge by discovering critical data points and trends that others miss.

The Role:

You will join our team of machine learning engineers developing the cutting edge AI & NLP systems that power AlphaSense Search. You are as excited about scaling these systems for production workloads as you are with developing cutting edge algorithms.


  • Develop highly scalable deep learning models
  • Adapt machine learning methods to make effective use of modern parallel environments, distributed clusters and GPUs
  • Define performance and scalability requirements for models in production and translate into technical implementation plan and roadmap
  • Own systems end-to-end including design, code, train, test, deployment and iteration


  • A BS/MS degree in Computer Science or Computer Engineering or equivalent
  • 4+ years developing data pipelines with Python with additional experience in Java, Linux, and scripting languages that interact with cloud resources
  • Demonstrated experience developing end-to-end NLP models to derive insights from text data using NLP libraries in Python
  • Experience with building back-end services and APIs in Django or Flask
  • Good grasp of data toolchains and best practices (such as Beam, Dataflow, Airflow, Spark, Kafka)
  • Experience with docker/kubernetes
  • Experience using SQL, NOSQL and search databases (SOLR/Lucene, MySQL, Mongo/Cassandra, SOLR/Lucene, etc.)
  • Experience working with cloud computing (preferably AWS or GCP)
  • Experience with iterative Agile methodology and use of tools like JIRA, Confluence, Git
  • Familiarity with Deep Learning frameworks like PyTorch and TensorFlow
  • Demonstrated experience in the software development lifecycle, from requirements to design to development and testing
  • Strong communication skills and ability to build pipelines with little guidance in small teams and independently
  • Excellent organizational, problem-solving, debugging and analytical skills
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