Technician instrumentation & control system Jobs

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AI Specialist

Bruker -
Bengaluru, Karnataka

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Job details

Qualifications

TensorFlow
CI/CD
Azure
Law
Computer Science
SAP
Salesforce
Master's degree
Analysis skills
Bachelor's degree
Continuous integration
SAP S/4HANA
Data science
AI
Python
Data Science

Full job description

Overview:

Bruker is enabling scientists to make breakthrough discoveries and develop new applications that improve the quality of human life. Bruker’s high-performance scientific instruments and high-value analytical and diagnostic solutions enable scientists to explore life and materials at molecular, cellular and microscopic levels. In close cooperation with our customers, Bruker is enabling innovation, improved productivity and customer success in life science molecular research, in applied and pharma applications, in microscopy and nanoanalysis, and in industrial applications, as well as in cell biology, preclinical imaging, clinical phenomics and proteomics research and clinical microbiology.

Today, worldwide more than +11000 employees are working on this permanent challenge at over 90 locations on all continents. Bruker continues to build upon its extensive range of products and solutions, its broad base of installed systems and a strong reputation among its customers. Being one of the world's leading analytical instrumentation companies, Bruker is strongly committed to further fully meet its customers’ needs as well as to continue to develop state-of-the-art technologies and innovative solutions for today's analytical questions.

Bruker India Scientific Pvt. Ltd is seeking for a AI Specialist to join their Bruker Nano Surfaces & Metrology (BNSM) division.

Responsibilities:

AI for Service Operations Excellence

Develop and deploy AI/ML solutions that directly reduce MTTR, improve first‑time‑fix, shorten ship‑to‑acceptance, and enhance customer experience through data‑driven automation and decision support.
Build predictive models for case intent, severity routing, escalation risk, and equipment‑specific failure patterns.

Salesforce & SAP Integration

Embed Generative AI and machine‑learning capabilities directly into Salesforce Service Cloud (desktop and mobile), including:
Agent‑assist
Automatic case summarization
Recommended troubleshooting steps
RAG (Retrieval‑Augmented Generation) with source citation
Integrate AI insights into SAP S/4HANA service processes including RMA, service contracts (ZISC), parts planning, and work‑order completion.

Knowledge Automation & Technical Support Enablement

Build RAG pipelines that provide technicians and support engineers instant access to approved manuals, OBQ/TQM data, troubleshooting procedures, escalation paths, and service knowledge.
Use AI to support structured problem‑solving (8D, DMAIC) by identifying patterns, failure modes, and likely root causes.
Call Center & Customer Contact Optimization
Deliver AI capabilities that increase case deflection, reduce AHT (Average Handle Time), improve FCR (First Contact Resolution), and raise CSAT/NPS.
Implement skill‑based routing models aligned to Salesforce queues and the formal escalation timeline.
Parts & Logistics Optimization
Develop forecasting and optimization models for service parts positioning, consignment strategy, RMA cycle time, depot stocking, and shipment prioritization for “down” systems.
Provide analytics to improve global 3PL performance and logistics visibility.
NPI (New Product Introduction) Readiness
Define AI‑readiness criteria for new product launches, including telemetry schemas, service knowledge packaging, and initial parts footprint modeling.
Ensure new products enter the field with search‑ready documentation and data for AI‑based troubleshooting.
Responsible AI, Compliance & Governance
Implement model governance, lineage, bias evaluation, and safety guardrails in alignment with Bruker’s Code of Conduct and IT Governance processes.
Ensure all AI solutions meet corporate standards for security, privacy, auditability, and global regulatory compliance.

Qualifications:

Bachelor’s or Master’s in Computer Science, Data Science, AI/ML, Engineering, or related field.
Strong experience building and deploying AI/ML models using Python and frameworks such as PyTorch, TensorFlow, or scikit‑learn.
Proven experience embedding AI into Salesforce Service Cloud workflows and integrating with SAP S/4HANA service processes.
Hands‑on experience with cloud AI platforms (Azure OpenAI preferred) and enterprise‑grade MLOps (model registries, CI/CD, drift detection).
Strong analytical skills with the ability to translate complex service problems into scalable AI solutions.

Preferred Qualifications

Experience applying AI in industrial, semiconductor, scientific instrumentation, or complex service environments.
Hands‑on experience with Generative AI, RAG, LLM evaluation, prompt engineering, and content‑safety controls.
Understanding of global service logistics, RMA workflows, contracting (ZISC), consignment strategy, and 3PL optimization.
Familiarity with NPI/service readiness deliverables and phase‑gate processes.

Bruker is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, national origin, disability, veteran status, and other protected characteristics.

Apply Now

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