Subject matter expert Steel Domain

HCL Technologies Limited; Wisconsin; In loco; USD 180.000 - 240.000; Tempo pieno

Descrizione del lavoro

HCL Technologies Limited is seeking a hands-on leader to steward steel manufacturing AI initiatives on the Core team, ensuring models reflect metallurgical realities from melt shop to wire and casting lines.

You will bridge operations and data science, validate domain feasibility, and drive adoption across mills, focusing on measurable improvements in yield, energy use, throughput, and quality while upholding safety.

Competenze

• 15+ years in steel or metals manufacturing operations or metallurgy.
• Deep command of steel process metallurgy and KPIs (yield, OEE, tap‑to‑tap, kWh/ton, electrode consumption).
• Practical working knowledge of manufacturing systems and automation and how data is generated and used.
• Proven record of driving measurable operational improvement on the plant floor.
• Credibility with plant leadership and frontline teams alike.
• Fluency with data, analytics, and AI to partner with data scientists (deep coding not required).

Mansioni

• Bring deep steel operations expertise to guide AI initiatives.
• Identify and prioritize AI use cases by operational value.
• Translate shop-floor problems into actionable statements for Pods.
• Own domain logic behind business cases and ROI validation.

Conoscenze

Steel operations expertise

Metallurgy knowledge

Manufacturing systems & automation

Operational improvement track record

Formazione

Engineering degree in metallurgical/materials/mechanical or related

Strumenti

MES

PI historians

SCADA / PLC

Level 1/2 automation

Descrizione del lavoro

The Office of AI has been established to lead the enterprise-wide adoption of artificial intelligence, advanced analytics, industrial automation, and Physical AI across the company's steel, wire, and casting operations. The Office runs a "Core & Flex" operating model: a central Core team sets the shared platforms, standards, and guardrails, while domain-aligned delivery Pods build and scale use cases close to the business. This role sits on the Core team and is a voting member of the AI Steering Committee — the cross-functional body, including the business-unit Presidents and enterprise leaders in Finance, HR, Operations, and Strategy, that sets AI priorities, approves investment, and governs risk. This is a hands-on leadership role for a proven operator, not a purely advisory seat.

Role Mission

You are the authoritative voice of steelmaking operations inside the Office of AI. You ensure that every use case, model, agent, and Physical AI deployment is grounded in metallurgical and operational reality — that the company builds AI that solves the problems that actually matter on the melt floor, the caster, the rolling mill, and the wire and casting lines, and that it delivers measurable results.

You are the bridge between the people who run the plants and the people who build the AI — and the enterprise's defense against solutions that look impressive but change nothing on the floor. You bring credibility that only comes from having run the operation.

Key Responsibilities

• Bring deep, first-hand steel operations expertise to the Office of AI, spanning melting (EAF), casting, rolling / rod, and downstream wire and cast-component operations.
• Identify, qualify, and prioritize AI and Physical AI use cases by operational value — yield, throughput, energy (kWh/ton), electrode and consumable use, quality and defect reduction, uptime, and cost — not by technical novelty.
• Translate shop-floor problems into clearly framed problem statements and success criteria the Pods can build against, and translate AI capabilities back into terms operators and plant leaders trust.
• Own the domain logic behind the business cases, so ROI figures are grounded, defensible, and validated against how the company's plants actually run.

Process & Metallurgical Validation

• Validate that models, agents, and twins respect process physics and metallurgy — that recommendations are feasible, safe, and metallurgically sound before they reach an operator or a control loop.
• Define the domain acceptance criteria and test scenarios AI systems must pass, including the edge cases known to experienced steelmakers.
• Serve as the domain check on data quality and semantics — knowing what a tag really means, when a sensor lies, and which signals actually matter.

Manufacturing Systems & Automation Expertise

• Bring practical command of manufacturing systems and automation — MES, historians (e.g., PI), Level 1/2 process automation, SCADA / PLC, and quality and lab systems — and of how data really flows (and breaks) on the plant floor.
• Advise the Architecture Lead on OT realities: latency, determinism, safety interlocks, and what can and cannot be touched by an automated or agentic system.
• Help specify Physical AI deployments — vision-based inspection and surface / defect detection, robotics and material handling, and real-time process twins — so they fit the harsh realities of a steel plant.

Operations Deployment, Adoption & Change

• Champion adoption on the floor — earn the trust of superintendents, operators, and process engineers, and ensure solutions fit the way work is really done.
• Lead operator-facing validation, pilot design, and the operational change required to move AI from pilot to standard practice.
• Capture and feed back operational learnings so solutions improve and scale across mills and business units.
• Serve as the shared steel-domain resource across Pods, ensuring consistency of operational assumptions and reuse of hard-won domain knowledge.
• Uphold the company's safety culture in every AI and Physical AI deployment, partnering with the Responsible AI Lead on Physical AI assurance.
• Mentor Pod members and analysts, raising the domain fluency of the whole Office of AI.

Required Qualifications & Experience

• 15+ years in steel or metals manufacturing operations, process engineering, or metallurgy, including hands‑on time running or directly supporting plant operations (melt shop, casting, rolling, or wire / finishing).
• Demonstrated, current command of steel process metallurgy and operations and the KPIs that drive them — yield, OEE, tap‑to‑tap, kWh/ton, electrode consumption, caster productivity, surface and internal quality, and mechanical properties.
• Practical working knowledge of manufacturing systems and automation (MES, historians, Level 1/2 automation, SCADA / PLC) and of how operational data is generated and used.
• A proven record of driving measurable operational improvement — yield, energy, quality, throughput, or cost — on the plant floor.
• Credibility with plant leadership and frontline teams alike, and the ability to translate between operations and technical teams.
• Enough fluency with data, analytics, and AI to partner effectively with data scientists and engineers (deep coding is not required).

Preferred Qualifications

• Direct EAF / electric‑steelmaking and continuous‑casting experience; familiarity with special‑bar‑quality (SBQ), rod, and wire operations.
• Exposure to AI / ML, computer vision, digital twins, or advanced process control applied in a live plant.
• Experience partnering with data‑science or automation teams on deployed solutions.
• A degree in metallurgical, materials, mechanical, or related engineering — advanced degree welcome, but secondary to operating experience.