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Remote Gas Engine Performance Engineer Jobs in Chicago, IL

CoSourcing Partners

GCP Gemini AI Developer

Chicago, IL · On-site +1

Remote / Hybrid - Chicago preferred Employment Type: Contract / Full-Time Reports To: GCP Technical ... Key Performance Outcomes (6-12 Months) Outcome What Success Looks Like Measurement 1. Gemini ...

Snapsheet

Senior Software Engineer

Chicago, IL · On-site +1

$135K - $165K/yr

USA, Remote Job Type: Full-time, direct hire About Snapsheet: Snapsheet is claims technology the ... Understanding of scalability challenges and performance of server-side code * Prior professional ...

Snapsheet

Senior Software Engineer

Chicago, IL · Remote

USA, Remote Job Type: Full-time, direct hire About Snapsheet: Snapsheet is claims technology the ... Understanding of scalability challenges and performance of server-side code * Prior professional ...

Loadsmart

Senior Embedded Systems Engineer

Chicago, IL · On-site +1

United States (Remote) WHAT YOU GET TO DO: * Maintain end-to-end system integrity across the ... AXIS cameras include the ARTPEC-8 chip with an onboard AI inference engine (Larod) and support ...

HONK

Senior Software Engineer - Fullstack

Chicago, IL · On-site +1

$160K - $185K/yr

This role works closely with the CTO and engineering team to develop high-performance applications ... As a remote-first company, we embrace the boundless possibilities of collaboration and flexibility ...

Honk

Senior Software Engineer - Fullstack

Chicago, IL · On-site +1

$160K - $185K/yr

This role works closely with the CTO and engineering team to develop high-performance applications ... As a remote-first company, we embrace the boundless possibilities of collaboration and flexibility ...

SDI International

Senior Site Reliability Engineer

Chicago, IL · On-site +1

$58.75 - $78/hr

Open to remote work in the US. The preferred work location is Chicago, IL. What You Might Work On ... Reliability & Performance Engineering * Improving the availability, scalability, and performance of ...

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All JobsRemote Gas Engine Performance Engineer JobsRemote Gas Engine Performance Engineer Jobs in Chicago, IL

Remote Gas Engine Performance Engineer information

See Chicago, IL salary details

$112.8K

$128.8K

$143.2K

How much do remote gas engine performance engineer jobs pay per year?

As of Jun 11, 2026, the average yearly pay for remote gas engine performance engineer in Chicago, IL is $128,768.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,000.00 and $136,500.00 per year, depending on experience, location, and employer.

What is the difference between Remote Gas Engine Performance Engineer vs Remote Gas System Analyst?

AspectRemote Gas Engine Performance EngineerRemote Gas System Analyst
Required CredentialsBachelor's in Mechanical or Electrical Engineering, certifications in engine testingBachelor's in Mechanical, Chemical, or Petroleum Engineering, certifications in gas systems analysis
Work EnvironmentDesign labs, field testing sites, remote monitoringData analysis, system modeling, remote diagnostics
Employer & Industry UsageEnergy companies, engine manufacturers, research institutionsOil & gas companies, utilities, engineering consultancies

The Remote Gas Engine Performance Engineer focuses on optimizing engine performance through testing and analysis, often working directly with engines. In contrast, the Remote Gas System Analyst specializes in analyzing and modeling gas systems remotely to improve efficiency and safety. Both roles require technical expertise but differ in their focus areas within the gas industry.

How does a Remote Gas Engine Performance Engineer typically collaborate with on-site teams to troubleshoot performance issues?

As a Remote Gas Engine Performance Engineer, you will regularly coordinate with on-site maintenance and operations teams using virtual tools such as video calls, remote monitoring systems, and shared diagnostic platforms. You may analyze real-time engine data remotely, guide on-site staff through troubleshooting steps, and provide recommendations for optimizing performance or resolving faults. Effective communication skills and the ability to interpret data while not being physically present are essential in ensuring smooth collaboration and timely problem resolution.

What are the key skills and qualifications needed to thrive as a Remote Gas Engine Performance Engineer, and why are they important?

To thrive as a Remote Gas Engine Performance Engineer, you need expertise in mechanical or automotive engineering, strong analytical skills, and a relevant engineering degree. Familiarity with engine diagnostic tools, performance monitoring software, and industry-standard modeling systems like MATLAB or GT-Power is typically required. Excellent problem-solving abilities, communication, and the capacity to work independently are standout soft skills in this remote role. These competencies are essential for accurately assessing engine performance, optimizing operations, and collaborating effectively with distributed teams.

What does a Remote Gas Engine Performance Engineer do?

A Remote Gas Engine Performance Engineer is responsible for monitoring, analyzing, and optimizing the performance of gas engines from a remote location. They use specialized software and data analytics to assess engine efficiency, diagnose issues, and recommend improvements to ensure optimal operation. Their work often involves collaborating with on-site engineers, providing technical support, and generating performance reports to help minimize downtime and maximize engine productivity.
What are the most commonly searched types of Gas Engine Performance Engineer jobs in Chicago, IL? The most popular types of Gas Engine Performance Engineer jobs in Chicago, IL are:
What are popular job titles related to Remote Gas Engine Performance Engineer jobs in Chicago, IL? For Remote Gas Engine Performance Engineer jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Remote Gas Engine Performance Engineer jobs in Chicago, IL look for? The top searched job categories for Remote Gas Engine Performance Engineer jobs in Chicago, IL are:
Remote Gas Engine Performance Engineer jobs near you

GCP Gemini AI Developer

CoSourcing Partners - Enterprise-AI and IT Services Company

Chicago, IL • On-site, Remote

Other

Posted 2 days ago

Job description

GCP Gemini AI Developer (3–5 Years Experience)

Location: Remote / Hybrid – Chicago preferred

Employment Type: Contract / Full-Time

Reports To: GCP Technical Lead / AI Program Manager

The GCP Gemini AI Developer will design, build, and deploy intelligent applications leveraging Google Cloud's Gemini models and Vertex AI platform. This role exists to operationalize advanced GenAI capabilities — including natural language understanding, multimodal reasoning, and generative automation — within scalable, secure, and production-ready cloud environments. The developer will work hands-on across data engineering, AI model orchestration, and API integration to create AI-driven business solutions that reduce manual effort, enhance decision-making, and unlock measurable value from enterprise data.

Key Performance Outcomes (6–12 Months)
  • Gemini-Powered Solutions Deployed: Design, develop, and deploy at least two Gemini-based AI solutions (e.g., document summarization, chat agent, or data extraction automation) using Vertex AI + Gemini APIs. Delivered to production with >90% accuracy and <2s response time.
  • Scalable Cloud Architecture: Build a modular AI microservices framework using Cloud Run / Cloud Functions with integrated authentication, logging, and monitoring. Reusable components adopted in at least 3 future use cases.
  • RAG / Context-Aware Workflows: Implement Retrieval-Augmented Generation (RAG) pipelines combining Gemini + BigQuery or vector databases for knowledge grounding. Demonstrated 25% reduction in hallucination or response variance.
  • Cross-Team Enablement: Partner with Data, Automation, and AppDev teams to integrate Gemini AI into existing business workflows (e.g., UiPath, Power Platform, or ServiceNow). Minimum of 2 successful integrations with documented ROI.
  • Continuous Optimization: Monitor, retrain, and improve AI models via Vertex AI pipelines and Model Monitoring. Demonstrated 15% performance gain over baseline models.
Core Responsibilities
  • Design and deploy Gemini 1.5 Pro/Flash integrations via Vertex AI and Generative AI Studio.
  • Build serverless APIs and backend services for AI workflows using Cloud Run, Functions, or App Engine.
  • Develop data ingestion and preprocessing pipelines using BigQuery, Dataform, and Pub/Sub.
  • Apply prompt engineering and parameter tuning to improve generative model accuracy.
  • Implement RAG pipelines leveraging Vertex Matching Engine or Pinecone.
  • Collaborate with automation and data teams to embed AI into existing business processes.
  • Maintain compliance with security, privacy, and model governance standards.
Technical Environment
  • Core Google Cloud Services: Vertex AI, Generative AI Studio, Gemini API
  • BigQuery, BigQuery ML, Dataform
  • Cloud Run, Cloud Functions, Cloud Storage
  • Pub/Sub, Secret Manager, IAM, Cloud Build
Programming Stack
  • Python or TypeScript (Google Cloud SDKs, google-generativeai, aiplatform)
  • FastAPI / Flask / Node.js
  • LangChain / LlamaIndex for orchestration
  • SQL, Pandas, and Jupyter for data prep
Complementary Tools
  • Terraform (IaC)
  • GitHub / GitLab CI/CD
  • Vertex AI Pipelines & Model Registry
  • Vector DB (Vertex Matching Engine, Pinecone, or Weaviate)
Ideal Profile
  • 3–5 years hands-on GCP development experience with AI/ML exposure
  • Strong working knowledge of Vertex AI, Gemini models, and RAG pipeline design
  • Demonstrated ability to move AI prototypes into production
  • Strong communicator, able to collaborate across automation, data, and cloud teams
  • Curious problem-solver passionate about applied AI innovation
Success Metrics
  • Speed to Delivery: End-to-end deployment within 8–10 weeks per use case
  • Model Effectiveness: >90% accuracy or relevance rating from business stakeholders
  • Scalability: Framework reused for ≥3 additional AI initiatives
  • Business Impact: 25%+ improvement in productivity or efficiency from deployed use cases

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