Machine Learning Engineer
Washington, DC
Sayari
Get instant access to public records, financial intelligence and structured business information on over 455 million companies worldwide.Our company culture is defined by a dedication to our mission of using open data to enhance visibility into global commercial and financial networks, a passion for finding novel approaches to complex problems, and an understanding that diverse perspectives create optimal outcomes. We embrace cross-team collaboration, encourage training and learning opportunities, and reward initiative and innovation. If you like working with supportive, high-performing, and curious teams, Sayari is the place for you.
What You Will Do:
Sayari’s flagship product, Sayari Graph, provides instant access to structured business information from hundreds of millions of corporate, legal, and trade records. As part of Sayari's data team you will work with our Product and Software Engineering teams to define Sayari AI architecture and AI strategy, and develop ML models to enrich our data, drive entity resolution, and enable AI features in Sayari Graph.
What You Will Need
- 4+ years of experience prototype-to-production AI/ML development; with demonstrated experience with classic machine learning models (e.g., Naive Bayes, Decision Trees, KNN, etc.), NLP (semantic embeddings), and LLMs (RAG, NLQ, agents, etc.)
- 4+ years of experience with Apache Spark and Spark ML, Apache Airflow, and ML/MLOps tooling (e.g., MLflow, Label Studio, etc.)
- Experience with Python and a JVM language (e.g., Scala)
- Experience working on with Google Cloud Platform
- Experience developing code collaboratively (git, testing, code reviews, etc.)
Preferred Qualifications
- Experience with Spark libraries such as GraphFrames, Spark NLP, cuGraph, etc.
- Experience with SQL and NoSQL databases (e.g., columns stores, graphs, etc.) and data warehouses (e.g., BigQuery).
- Experience with Docker/Kubernetes
- Experience managing and mentoring team members
Education
- Advanced degree in Computer Science, Statistics, Engineering, or other quantitative disciplines.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow AI strategy Architecture BigQuery Computer Science Docker Engineering GCP Git Google Cloud Kubernetes LLMs Machine Learning MLFlow ML models MLOps NLP NoSQL Python Scala Spark SQL Statistics Testing
Perks/benefits: Career development Competitive pay Equity Flex hours Flex vacation Health care Parental leave Startup environment
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