Position Summary:
Knorr-Bremse, the global leader in braking systems and rail/vehicle safety solutions, is building its AI Center of Excellence in Chennai to accelerate innovation across its Rail and Truck business.
We are seeking a visionary Generative AI Scientist to act as the crucial bridge between complex business challenges and the frontiers of artificial intelligence. This is a role for a lead/senior applied scientist who not only understands the deep, foundational principles of AI but can also critically assess its practical limitations and business viability.
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The ideal candidate combines the mind of a researcher with the pragmatism of a business strategist, capable of translating a business need into a technical hypothesis and owning the outcome from conception to post-deployment success.
Essential Functions:
Translate Business Challenges into Viable AI Solutions:
Lead feasibility studies for proposed AI applications (e.g., General & Administrative (G&A) work, Domain Specific Compliance Checks like mobility compliance adherence, AI application in manufacturing). Translate ambiguous business requirements into precise technical problems and hypotheses.Conduct comprehensive literature surveys, reviewing academic papers and patents to inform solution design and identify state-of-the-art approaches.Critically Assess AI Feasibility and Limitations:
Serve as the expert on the practical boundaries of LLMs and Generative AI. Identify risks and clearly articulate what aspects of a problem are well-suited for current AI capabilities and which are not, preventing investment in unfeasible projects.Design Authority
: Own end-to-end technical and process design for AI/ML and agentic AI solutions, ensuring alignment with business objectives and scalability across Knorr-Bremse’s global operations. Design and build proof-of-concept systems based on a first principles understanding of Advanced RAG, multi-agent architectures, and fine-tuning techniques. Develop rigorous evaluation frameworks to benchmark system performance against business-relevant metrics.Hands-on AI Development
: Drive research and development in areas such as agentic AI frameworks, computer vision, multimodal learning, time-series optimization, and generative AI for embedded and industrial applications.Innovation & IP Creation
: Develop cutting-edge algorithms, publish high-impact research, and contribute to patents/IP that strengthen Knorr-Bremse’s technological leadership.Mentorship & Team Leadership
: Lead, mentor, and inspire a team of AI scientists and engineers; build a high-performance research culture that bridges academia and industry.Entrepreneurial Execution
: Champion rapid prototyping, proof-of-concept development, and large-scale deployment of AI solutions in collaboration with cross-functional teams (R&D, IT, Cloud, Security, Business).Collaboration & Scaling
: Work closely with internal stakeholders and technology partners (AWS, Microsoft, Google) to leverage multicloud AI stacks for scalable deployment.Governance & Best Practices
: Establish standards for AI design, evaluation, and deployment, ensuring robust, ethical, and cost-efficient AI solutions.
Skills:
Technical & Scientific Skills:
Foundational AI Expertise
: Profound understanding of transformer architectures, attention mechanisms, and the theoretical underpinnings of LLMs.
Critical Assessment of Model Capabilities
: Deep, practical knowledge of the inherent limitations of LLMs (e.g., factual consistency, complex reasoning, susceptibility to hallucination, handling of structured data) to accurately determine problem feasibility.
Expertise in RAG and Fine-Tuning
: Mastery of the mechanics of RAG (dense/sparse retrieval, re-ranking) and various fine-tuning methods (PEFT, LoRA), including their theoretical trade-offs.Research Acumen
: Proven ability to rapidly consume, critique, and synthesize information from academic papers and patents to inform practical solutions. Multiple patents, peer-reviewed publications.Strong Programming & Foundations
: Python (Expert); strong grasp of algorithms and system design. Strong expertise in Agentic AI frameworks (Google ADK, MCP Agent, LangGraph, etc.) and LLM vendors (Azure OpenAI, Google Gemini, etc.). Proficiency in deep learning & ML frameworks (PyTorch, Scikit-learn, MLFlow, Vertex AI, Kubernetes).
Behavioral Competencies:
Business Acumen & Pragmatism:
A strong ability to connect technical possibilities with business value, balancing innovation with practical constraints, costs, and timelines.First-Principles Thinker:
A deep-seated curiosity to understand *why* systems work and fail, enabling robust problem diagnosis and solution design.Intellectual Honesty:
The confidence to advise against a project when the technology is not a good fit, and the ability to clearly articulate the risks and unknowns.Ownership Mentality:
A proactive, accountable approach to the entire project lifecycle, from initial idea to long-term performance.Excellent Communication:
Can articulate complex technical concepts, business justifications, and system limitations to audiences ranging from engineers to senior executives.
Strong communication and stakeholder engagement skills
Experience:
- Experience: 7-12 years of applied AI/ML research and development, with proven impact in industrial, mobility, or large-scale enterprise settings.
- Track record of patents, publications, or IP creation in AI/ML.
- Strong team leadership and mentoring experience.
- Entrepreneurial, innovative, and execution-focused mindset.
- Proven track record of leading AI projects from business concept to production.
- Demonstrable experience conducting feasibility studies and translating business requirements into technical AI roadmaps.
Education:
- Education: Master’s or PhD in Data Science, AI/ML, Operations Research, Computer Science, or related fields (IIT/IIM or equivalent preferred).
Position Requirements:
- Ability to travel up to 25% domestically and internationally.
What We Offer
- A unique opportunity to shape the future of AI in mobility and safety-critical systems, backed by a team that respects deep technical and strategic expertise.
- An innovation-driven environment with strong academic and industry collaboration.
- Exposure to global-scale AI projects spanning truck, rail, and industrial domains.
- Own the end-to-end lifecycle of AI initiatives, from initial business concept to tangible, value-driving deployment.
- Operate at the intersection of business strategy and deep technology, making critical decisions that shape our AI roadmap.
- Solve high-stakes problems in a research-driven environment that values intellectual honesty and pragmatic results.
