Co Op Computer Science Jobs in Tulsa, OK (NOW HIRING)

Job Summary:
Targa Resources is a company focused on integrating artificial intelligence and emerging technologies into operational processes. The Principal Engineer will lead the evaluation and adoption of these technologies to enhance operational efficiency and asset reliability while collaborating with various internal and external teams.
Responsibilities:
• Lead identification, prioritization, and piloting of new technologies that include AI/ML, digital twins, generative AI, equipment upgrades and autonomous inspection technologies across operational assets.
• Maintain a prioritized backlog of AI and Emerging Technology use cases mapped to organizational KPIs (e.g., corrosion growth rates, MTBF for rotating equipment).
• Partner with SCADA and Measurement teams to build reliable real-time data pipelines for AI and Emerging Technology model deployment.
• Coordinate with internal and external resources to develop, test, and deploy AI/ML models.
• Provide tracking and regular updates on testing progress; interface with testing groups to maintain strong communication and clear issue/decision logs.
• Support investment partners to scout startups and technology partners; translate business pain points into clear technical needs, screen solutions quickly, and maintain a pipeline of high-potential opportunities.
• Lead technical diligence for venture and partner opportunities (architecture, data flows, cybersecurity posture, scalability, reliability, integration approach, vendor maturity, and technical risk) to inform investment and partnership decisions.
• Define pilot/POC scope, success criteria, test plans, and measurement approach for venture-backed or partner solutions (KPIs, value realization, safety/compliance impacts, and operational readiness); run disciplined stage-gates from prototype through field pilot to scale decision.
• Own day-to-day technical partnership execution during pilots and post-investment: coordinate internal stakeholders and startup/partner teams, manage technical deliverables, resolve blockers, and ensure successful handoff into steady-state operations with clear ownership and support models.
• Drive structured feedback loops with startups/partners to influence product roadmap and co-development (requirements, data access, field learnings, defect triage, and release validation) aligned to Targa standards.
• Partner with IT/OT and platform teams to operationalize MLOps practices (model/version control, reproducible training, automated testing, deployment pipelines, and documentation).
• Establish and track KPIs and cost/benefit analyses for AI and Emerging Technology initiatives, present findings and recommendations to senior leadership.
• Support change management and training efforts to improve AI and Emerging Technology literacy across the organization.
• Collaborate with EAM, Reliability, MI, Corrosion, OT/SCADA, and Pipeline Integrity teams to align AI and Emerging Technology initiatives with business needs.
• Drive cultural adoption of AI/Emerging Technology through rapid prototyping and feedback loops.
• Ensure AI/Emerging technology initiatives support and align with operational goals related to safety, compliance, reliability, and efficiency.
• Engage with Commercial, Engineering & Construction, and ES&H teams to align AI/Emerging Technology efforts with broader strategic objectives.
• Conduct field visits to evaluate technology adoption and identify opportunities for improvement.
• Serve as SME for monitoring, maintenance, and continual development of deployed AI and emerging technologies.
• Perform other duties as assigned.
Qualifications:
Required:
• Bachelor’s degree in Engineering, Computer Science, Data Science, or related field (or equivalent industry experience).
• 7+ years of experience in midstream oil & gas or industrial operations a with role focused on operations, technology, or innovation.
• Proven experience deploying AI/ML solutions in operational environments.
• Strong understanding of Operating Equipment, SCADA, Maximo, Measurement, and asset performance systems.
• Excellent communication, leadership, and decision-making skills.
• Ability to travel frequently across Targa’s operational regions and respond to urgent matters outside standard business hours.
• Familiarity with regulatory frameworks (DOT/PHMSA, EPA, OSHA) and how AI & Emerging Technology can support compliance and performance.
• Familiarity with pipeline, compressor, gas plant, and fractionator operations and how AI & Emerging Technology can support enhanced performance.
Preferred:
• Vision to see what can be, with the knowledge to understand deployment limitations.
• Field engineering and operational background.
• Experience working with startups/partners (scouting, evaluation, pilots/POCs, and scale-up), including navigating ambiguity and fast iteration cycles.
• Experience supporting investment diligence by translating technical findings into clear decision inputs (technical risks, integration effort, security/data considerations, and scaling path) for business stakeholders.
• Experience designing testing and acceptance strategies for new technology deployments (requirements, integration testing, cybersecurity considerations, UAT, and operational readiness reviews).
• Ability to define and track KPIs/value realization for pilots and deployments, including building basic dashboards/scorecards and leading root-cause analysis when outcomes drift from targets.
• Strong vendor/partner evaluation skills, including reviewing architectures, security posture, data handling, support models, and SLA/operational requirements.
• Working knowledge of data/AI and automation tooling (e.g., Python, APIs, cloud/edge platforms) and concepts such as model/version governance, system integration, and change management.
Company:
Targa is a leading provider of midstream services as one of the largest independent midstream infrastructure companies in North America. Founded in 2005, the company is headquartered in Houston, USA, with a team of 1001-5000 employees. The company is currently Late Stage.