Job Type:** Full-time

Experience Required:** 12–20 years

About the Role

We are looking for a senior technical leader to own our enterprise AI strategy and architecture. You will design and scale production-grade deep learning and generative AI systems, build robust MLOps infrastructure, and lead high-performing AI/ML teams that deliver measurable business impact.

Key Responsibilities

**AI Strategy & Architecture**

- Partner with CEO, CTO, and Product leadership to define the multi-year AI roadmap and prioritize high-ROI initiatives

- Architect large-scale deep learning systems (Transformers, LLMs, Diffusion models, multimodal architectures) using PyTorch and TensorFlow

- Drive adoption of Generative AI solutions including RAG pipelines, vector databases, fine-tuning, and agentic systems

- Set technical standards for the Python data science stack and ensure seamless integration with production systems

**MLOps, Infrastructure & Scale**

- Design and own distributed training infrastructure (multi-GPU/multi-node) using tools such as DeepSpeed, Ray, or Horovod

- Build and govern the full MLOps lifecycle: data pipelines, model registry, automated evaluation, continuous deployment, and monitoring

- Optimize inference performance and cost using TensorRT, ONNX, quantization, and distillation techniques

- Define cloud architecture strategy on AWS SageMaker, GCP Vertex AI, or Azure ML, including GPU cost governance

**Leadership & Governance**

- Hire, mentor, and lead a team of Principal ML Engineers, Applied Researchers, and Data Scientists

- Establish AI governance standards covering model risk, bias mitigation, explainability, data privacy, and regulatory compliance

- Drive applied research, patent filings, and strategic technology partnerships

- Communicate AI strategy,



risks, and ROI clearly to executive leadership and the board

Required Qualifications

- 12–20 years of experience in software engineering, data science, and applied machine learning, including 8+ years shipping deep learning systems to production

- Expert-level proficiency in Python and production experience with PyTorch and/or TensorFlow

- Deep hands-on experience with modern transformer architectures, LLMs, and at least one additional domain (Computer Vision, Speech, Reinforcement Learning, or multimodal systems)

- Proven ownership of MLOps platforms and distributed training/inference infrastructure on Kubernetes and GPU clusters

- Strong experience with at least one major cloud platform (AWS, GCP, or Azure) and container orchestration (Docker/Kubernetes)

- Experience with large-scale data systems (Spark, Ray) and vector databases (Pinecone, Milvus, Qdrant, pgvector, etc.)

- Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field preferred

Preferred Skills

- Solid business judgment with the ability to evaluate GPU/cloud costs against measurable value

- Track record of moving research prototypes into reliable, monitored production systems

- Excellent communication skills with experience presenting to C-level executives and boards

What We Offer

- Competitive executive compensation package (base salary + performance bonus + significant equity)

- Dedicated budget for GPU infrastructure, R&D;, and top-tier conferences (NeurIPS, ICML, CVPR)

- High autonomy and the mandate to shape the company’s AI strategy

- Flexible hybrid/remote working arrangements

---

**Ready to apply?**

Please submit your resume and a brief note on relevant AI architecture or leadership experience.

Work Location: In person

📌 Chief AI Architect / VP of AI & Machine Learning (Hyderabad)
🏢 D&D CLOUD
📍 Hyderabad