Mid-Level Machine Learning Engineer [$264k/yr+] TS/SCI-FS Poly
SYSTOLIC, INC.
Herndon, VA, United States
8 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
8 years minimum
Compensation
$264,000.0
Working hours
Regular working hours
Job source
Tech stack
JavaScript (Programming Language)
Artificial Intelligence
Apache HTTP Server
Big Data
Cloud Computing
Information Engineering
Extract Transform Load (ETL)
Web Development
Elasticsearch
Apache Hive
PostgreSQL
Machine Learning
+11 more
Neo4j
Node.Js
SQL Databases
Web Applications
Web Application Frameworks
ReactJS
Apache Spark
Git
Atlassian Tools
Kibana
Data Pipelines
Job description
- Deploy robust web applications, construct resilient ETL data pipelines, and build advanced AI/ML solutions to accelerate analytic workflows.
- Enable stakeholders to derive key insights from large-scale data stores using modern open-source technologies.
- Collaborate within a multidisciplinary team of data scientists, engineers, and application developers., * Develop and deploy web applications utilizing modern frameworks including React.js, Node.js, and JavaScript.
- Build resilient data engineering and ETL pipelines leveraging Trino, Apache Iceberg, PostgreSQL, SQL, Apache Spark, Neo4j, Elasticsearch, Kibana, and Apache Hive.
- Implement deliverables leveraging state-of-the-art AI/ML models and data science workflows.
- Maintain cloud infrastructure and support system accreditations for platform-hosted production applications.
- Manage code and infrastructure repositories in Git while tracking project tasks using Jira and Confluence.
- Provide technical guidance and subject matter expertise across AI/ML, web application development, and ETL.
- Ensure all technical deliverables and content adhere strictly to applicable security policies and regulations.
Requirements
- Degree: Technical bachelor’s degree or equivalent experience
- Years of experience: 8+ years
- Total Compensation: $264k+ yearly (tentative)
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