Data Engineer

Company Overview

At Cynnovative, we leverage machine learning, computer science, and software engineering to address high-impact problems in the cyber domain, specifically those which are critical to U.S. national security. We primarily extend fundamental research to invent, design, develop, and deploy prototype solutions that support persistent problems in this domain.

Job Overview

Data scientists and engineers at Cynnovative play a key role in our integrated, multi-disciplinary teams, providing statistical, methodological, and analytical support as well as machine learning expertise. As a data engineer, you will transform data into a useful format for analysis by our data scientists who apply methods ranging from basic statistics to state-of-the art machine learning techniques and cutting-edge research to protect people, networks, and devices from cyber threats. While Cynnovative’s research is broadly defined, you can anticipate frequent opportunities to gain domain expertise in a cyber-related field during the course of normal duties.

This is a research and development role. The ideal candidate is experienced with architecting distributed systems, creating reliable pipelines, combining data sources, and collaborating with data scientists and building the right solutions for them. Because Cynnovative interfaces with operational users and aspires to create practical solutions, the ideal candidate is similarly comfortable developing and deploying prototypes while addressing the practical issues inherent in operational scenarios, such as sparse or messy data. As a growing company, Cynnovative offers many leadership opportunities, including as principal investigators of future projects.

May Include

  • Collaborating with data scientists to develop and optimize data ingest, transformation, and storage solutions that will enable machine learning on large datasets
  • Developing, deploying, and maintaining data pipelines and databases
  • Discovering and demonstrating technology solutions to support novel research in the cyber domain
  • Designing and deploying machine learning algorithms in the course of R&D activities
  • Documenting and presenting findings and technical results

Must Have

  • M.S. in a quantitative field or B.S. with 2+ years of experience
  • High fluency in Python (5+ years of experience)
  • Fluency in Java or C++ (3+ years of experience)
  • Experience developing data ontologies, data schemas, and database designs
  • Experience leveraging cloud services, specifically Amazon Web Services (AWS)
  • Experience with Kubernetes or similar deployment mechanisms
  • Experience with Apache Airflow or Apache NiFi
  • Excellent oral and written communication skills
  • Ability to work as part of a remote team
  • U.S. Citizenship and an active TS/SCI security clearance

Please note that per Executive Order 14042, a requirement of this position is that employees are fully vaccinated or have an approved accommodation on file. If you are applying to this position, you attest that you are 1. Fully vaccinated; 2. Intend to be vaccinated 60 days after accepting the position; or 3. Will apply for a medical or religious accommodation that must be approved prior to the start of the position. If you are not approved for an accommodation, the employee must then state their intent to be vaccinated in 60 days or the offer will be rescinded.

Desired Skills
Nice To Have

  • Experience developing or deploying solutions in classified environments
  • Experience with performance tuning MinIO or other Object stores
  • Experience with cyber-related research
  • Experience with machine learning

Cynnovative is committed to creating a diverse environment and is proud to be an equal opportunity employer. Cynnovative recruits, employs, trains, compensates and promotes regardless of race, religion, color, national origin, sex, disability, age, veteran status, and other protected status as required by applicable law.

Please send resumes and inquiries to [email protected] with the position title in the subject line.