Job Summary

Architect Enterprise AI Scale as Staff AI/ML Operations Engineer.

Are you a seasoned technical authority ready to define the strategic direction of enterprise AI/ML infrastructure and shape the future of MLOps across a global technology leader Trimble is seeking a visionary Principal AI/ML Operations Engineer (P4/P5) to join our Construction Management Solutions (CMS) team in Chennai. In this premier technical leadership role, you will set organizational vision, architect next-generation machine learning platforms, and establish industry-defining operational practices that scale across diverse enterprise business units.

What Makes This Role Great

Operating at the highest technical tier within Trimble CMS, you will have the mandate to drive multimillion-dollar, transformational AI/ML initiatives from the ground up. You will not simply manage workflows; you will design and implement the foundation for real-time distributed inference, edge AI deployments, and foundation model serving across thousands of production models. Working out of our Chennai engineering hub with executive sponsorship, you will represent Trimble at premier industry conferences, mentor high-performing staff-level engineers, establish strategic research partnerships, and lead our global transition toward autonomous MLOps and Zero Trust AI security.

Key Exciting Responsibilities

- Enterprise ML Vision Platform Architecture: Define the multi-year technical roadmap for enterprise AI/ML infrastructure, architecting unified platforms capable of serving thousands of models with sub-second latency across diverse business units.
- Cutting-Edge MLOps Deployment: Implement advanced MLOps solutions, including automated hyperparameter optimization, neural architecture search (NAS), model quantization, and distributed serving architectures supporting millions of predictions.
- Next-Gen AI Foundation Models: Architect scalable infrastructure for emerging generative technologies,



including Large Language Models (LLMs), multi-modal systems, prompt-engineering pipelines, and federated learning frameworks.
- Observability, Self-Healing Security: Engineer comprehensive ML observability stacks featuring custom telemetry, drift detection, automated anomaly mitigation, Zero Trust architectures, and model privacy preservation.
- Strategic Governance Centers of Excellence: Establish cross-organizational MLOps governance, compliance standards, and A/B or multi-armed bandit experimentation frameworks across multiple engineering hubs.
- Executive Influence Thought Leadership: Partner directly with C-suite leadership and product executives to align technology investments with business outcomes, while representing Trimble through patents, publications, and open-source contributions.

Essential Skills Experience

- Education: Advanced degree (Master's or PhD) in Computer Science, Machine Learning, Engineering, or a related technical discipline (or equivalent skilled experience with exceptional technical depth).
- Professional Experience: 8+ years of dedicated experience in MLOps, Machine Learning Engineering, or Site Reliability Engineering (SRE), with at least 3+ years operating in senior/principal technical leadership capacities.
- Large-Scale Inference Systems: Proven track record architecting and maintaining large-scale ML infrastructure serving millions of daily predictions with high availability and extreme fault tolerance.
- Polyglot Systems Mastery: Expert programming capabilities across multiple modern languages (Python, Go, Rust, Java,



or C++) paired with deep expertise in distributed computing, concurrency, and performance tuning.
- Multi-Cloud Transformation: Extensive experience architecting cloud solutions across AWS, Azure, or GCP, leveraging advanced AI/ML managed services while enforcing rigorous FinOps cost optimization.
- ML Lifecycle Experimentation: Deep expertise managing end-to-end ML lifecycles at scale, including automated experimentation, feature stores, model registries, and sophisticated rollout frameworks.
- Modern Infrastructure Tooling: Practical mastery of advanced cloud-native infrastructure including Kubernetes, service mesh architectures (Istio), event-driven streaming (Kafka), and serverless ML pipelines.

Bonus Points For

- Generative AI Systems: Direct experience operationalizing transformer architectures, foundation model fine-tuning (LoRA, QLoRA), and enterprise-grade vector database retrieval infrastructure.
- Advanced Data Engineering: Familiarity with real-time streaming pipelines, Data Mesh paradigms, and privacy-preserving data analytics.
- Compliance Governance: In-depth knowledge of model explainability/interpretability frameworks, bias mitigation tools, and regulatory guidelines (GDPR, CCPA, EU AI Act).
- Industry Prominence: Published academic research, registered patents, or prominent contributions to open-source MLOps toolkits.
- Emerging Architectures: Familiarity with neuromorphic hardware, specialized AI accelerators (TPUs/NPUs), or quantum computing paradigms.

Logistics

- Grade / Level: P4
- Location: Chennai, India
- Department: Construction Management Solutions (CMS)
- Job Type: Full-Time

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Staff Agentic Artificial Intelligence Engineer (Chennai)
🏢 Trimble
📍 Chennai