Machine Learning Engineer - AI Research at AlphaSense
AlphaSense provides a revolutionary search engine for knowledge professionals.
Our mission is to curate and summarize the world's business knowledge, including the vast high-value content sets that traditional web search engines cannot reach. Our users can rapidly discover key data points & relationships while tracking impactful real-time events with intelligent, automated alerts.
Our 1000+ clients include many of the world's largest investment & advisory firms, global banks & Fortune 500 corporations - helping our users become dramatically more productive & gain an information edge by discovering critical data points & trends that others miss.
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