Machine Learning Engineer

Washington, DC

Sayari

Get instant access to public records, financial intelligence and structured business information on over 455 million companies worldwide.

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About Sayari: Sayari is the counterparty and supply chain risk intelligence provider trusted by government agencies, multinational corporations, and financial institutions. Its intuitive network analysis platform surfaces hidden risk through integrated corporate ownership, supply chain, trade transaction and risk intelligence data from over 250 jurisdictions. Sayari is headquartered in Washington, D.C., and its solutions are used by thousands of frontline analysts in over 35 countries.
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.
Benefits: ·       Limitless growth and learning opportunities·       A collaborative and positive culture - your team will be as smart and driven as you·       A strong commitment to diversity, equity & inclusion·       Exceedingly generous vacation leave, parental leave, floating holidays, flexible schedule, & other remarkable benefits·       Outstanding competitive compensation & commission package·       Comprehensive family-friendly health benefits, including full healthcare coverage plans, commuter benefits, & 401K matching Sayari is an equal opportunity employer and strongly encourages diverse candidates to apply. We believe diversity and inclusion mean our team members should reflect the diversity of the United States. No employee or applicant will face discrimination or harassment based on race, color, ethnicity, religion, age, gender, gender identity or expression, sexual orientation, disability status, veteran status, genetics, or political affiliation. We strongly encourage applicants of all backgrounds to apply.
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* 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

Region: North America
Country: United States
Job stats:  8  1  0

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