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AI Operations Engineer

4 months ago

Palo Alto, United States Brain Gain Recruiting Full time
Job DescriptionJob DescriptionCompany Description

This is a unique opportunity to get on a team of an Industrial AI start-up founded by a Stanford professor and led by recognized thought leaders in AI/ML and aerospace analytics.

Our main product is enterprise SaaS for supply chain in aircraft fleet maintenance. The product is built around proprietary AI Engines and allows for easy customers data integration.

The company has won substantial repeat business from US Air Force Supply Chain operations that sustains the world largest aircraft fleet. We are looking to leverage our proven military customer product into substantial growth in the short term, and an M&A exit in the medium term. We are a technology leader in Enterprise AI for supply chain with strong customer pull and the probability of fast win is high.

Job Description

The ‘Rocket Science’ processes for our mission-critical Explainable AI (xAI) involve rigorous cross validation of data, AI testing, verification, and validation. Custom developed AI/ML algorithms are packaged as integrated AI Engines. Our lean team is looking for an AI Operations Engineer who will be ultimately responsible for the AI Engines, their integration in the cloud app product, and customer interfaces.

A successful candidate will understand what our app does, customer business cases, how the AI works, and help make feature development and DevOps processes work smoothly. Depending on the interests and experience, this position may become more data engineering, AI Engines, customer business, cloud computing, or product management oriented.

You will start in a part-time consulting position at a competitive hourly rate. As your contributions add up and the business grows, you will have an opportunity to transition to full-time.

 

Main Responsibilities:

  • Develop and support AI Engines using core AI functions. This includes AI results presentation, internal and external interfaces, engineering documentation, and AI customization to address customer issues.
  • Support data engineering, data consistency checking, and preprocessing pipelines that produce AI metadata from raw data
  • Support scalable AI deployment. The analytics pipeline includes aerospace grade algorithm verification | test coverage | reporting logic | compilation and build. It produces object code and resource files that feed into DevSecOps pipeline for cloud app.
  • Interface with and support cloud software team that deals with Analytics Engine as a black box with well-defined API.
  • Occasionally interface with customers on data issues, analysis result interpretation, and, eventually, on business value of the AI analytics.
  • Document and coordinate improvement for components, products, and processes.
Qualifications

Must-haves

  • Degree in Engineering, Applied Math, Computer Science, Physics, or a similar discipline, from a top school.
  • 5+ years of industry experience with analytical applications including experience with developing and maintaining analytical code base.
  • Strong MATLAB experience
  • Ability to produce thorough documentation as evidenced by academic, research, professional, or industry publications. Examples are graduate theses or technical papers. GitHub contributions might be substituted for technical publications.
  • Rigor and attention to detail necessary for development of mission critical mathematical software.
  • Java code maintenance experience
  • Experience with GitHub including GitHub Actions
  • Excellent communication and collaboration skills
  • US Citizenship

Pluses

  • Experience with some of the following: statistics, optimization, controls, signal processing, applied math, and related practical applications
  • Familiarity with model-based development and simulation-based verification
  • Shell scripting


Additional Information

  • US Citizenship Required: This position requires the ability to work with Controlled Unclassified Information for the Department of Defense.
    Location: This is a remote position. USA, Nationwide. Proximity to either our Palo Alto, CA or Atlanta, GA office is a plus.

    Flexible schedule: full-time or part-time but no less than 10 hours/ week.