Research Engineer

Factagora; Republic (MO); Hybrid; USD 90,000 - 140,000; Full time

Job summary

Factagora in the United States invites an engineer to transform research into real products using the Temporal Knowledge Graph. You will develop production APIs and services focused on time-series forecasting, pattern analysis, and anomaly detection.

You'll bridge experimental code and product code, design data-driven experiments, and collaborate with the engineering team and the CEO to mature the research‑to‑product cycle, supporting the global R&D program.

Qualifications

• 2+ years of software development experience or equivalent practical ability.
• Ability to turn research ideas into working code and systems.
• Excellent documentation and clear technical writing.

Responsibilities

• Applied research and algorithm design using the Temporal Knowledge Graph.
• Research on forecasting models, pattern analysis, and anomaly/risk/opportunity detection logic based on time-series and ontology data.
• Turning research outcomes into production-ready APIs and code for real services.
• Acting as the bridge between experimental code and product code.
• Designing data-driven experiments and validating performance through comparison.
• Collaborating with the engineering team and the CEO to mature the research-to-product cycle.
• Supporting research and technical validation for our global R&D TIPS program.

Skills

2+ years software development

Experimentation

Technical writing

Education

Master's or PhD in time-series analysis, ML, graphs, statistics, or related field

Tools

Python

Java

Scala

Knowledge Graphs

Graph DBs

Job description

An engineer who turns research into real products

You'll lead applied research and product feature development built on our Temporal Knowledge Graph. Rather than focus on core system design, you'll use this technology to research high-value capabilities such as time-series forecasting, pattern analysis, and risk and opportunity detection, and implement them directly as production APIs and services.

Responsibilities

• Applied research and algorithm design using the Temporal Knowledge Graph
• Research on forecasting models, pattern analysis, and anomaly/risk/opportunity detection logic based on time-series and ontology data
• Turning research outcomes into production-ready APIs and code for real services
• Acting as the bridge between experimental code and product code
• Designing data-driven experiments and validating performance through comparison
• Collaborating with the engineering team and the CEO to mature the research-to-product cycle
• Supporting research and technical validation for our global R&D TIPS program

Requirements

• 2+ years of software development experience, or equivalent practical ability
• Experience writing production service code in at least one language such as Python, Java, or Scala
• Solid understanding of at least one of: data processing, algorithms, or system implementation
• Experience turning research ideas into working code and systems
• Ability to quickly grasp new technologies and domains and translate them into experiments and implementation
• Comfortable writing documentation and structuring technical content clearly

Preferred Qualifications

• A master's or PhD (or equivalent research experience) in time-series analysis, machine learning, graphs, statistics, or a related field
• Practical or research experience with Knowledge Graphs, Graph DBs, ontologies, or semantic technologies
• Direct experience designing and implementing projects in time-series forecasting, anomaly detection, or pattern analysis
• Experience applying research outcomes to a real product or service
• Experience participating in global R&D or government-funded research programs
• Experience collaborating on a small team in an early-stage startup or deep-tech environment

Who We're Looking For

• You're excited by the process of turning research into real products and user value
• You don't stop at papers or ideas; you want to see things through to implementation
• You value "it runs in production" over "it's theoretically possible"
• You break complex problems into structured pieces and work through them with calm, careful experimentation
• You connect with Factagora's mission (trustworthy AI) and want to grow with us technically for the long term

Hiring Process

Application 1st Interview 2nd Interview Final Offer

Application Inquiries

If you run into any issues during the application process or have questions about this role, reach out to
[e-mail] and we'll get back to you as soon as possible.