Job Title

Job Profile- Designation- Principal Engineer - AI/ML (10-15 YOE)Location- HyderabadMode of work- 5 days office based jobNotice Period- Not more than 45-60 DaysJD-Principal Engineer - AI/MLB.E/B.Tech/M.Tech/M.E degree in Computer Science or equivalent10-12 years of industry experience in applied AI/GenAI, designing and developing scalable enterprise level solutionsExperience in architecting and building large, highly scalable systems & software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, agentic workflows, prompt orchestration)Strong programming (Python / C++ or equivalent) and data engineering skillsDeep understanding of Generative AI best practices (e.g., prompt engineering, RAG, agentic design, model fine-tuning, optimization), LLMs, multimodal models, and deep learning basics.Experience with these technologies: OpenAI GPT, Llama, Hugging Face Transformers, LangChain, DeepSpeed, Ray, Kubernetes, Spark, Kafka (or equivalent).Industry experience building end-to-end GenAI infrastructure and/or building and productionizing Generative AI models, agents, and workflowsExperience with MLOps/LLMOps practices and tools (e.g., MLflow, Weights & Biases, DVC, SageMaker, Vertex AI)Design, implement and integrate the next generation of Generative AI infrastructure to empower other Data Scientists and AI engineers to build GenAI models and agents that make real-time decisions.You will collaborate with other engineers and data scientists to create optimal experiences on the Core GenAI platform, including but not limited to: prompt libraries, agentic orchestration, the real-time serving layer, and the offline training systemStrong collaboration and communication skills, both verbal and writtenBring a deep empathy for customer needs and insights as well as an intuitive grasp of the business problems we’re trying to solveGood to have:Experience with traditional machine learning and deep learning frameworks and algorithms (e.g., RNNs, CNNs, Transformers, GANs)Knowledge of reinforcement learning, transfer learning, and meta-learning conceptsHands-on experience with TensorFlow, PyTorch, JAX, KerasFamiliarity with data labeling platforms, ML model monitoring and evaluation toolsExperience with MLOps/LLMOps practices and tools (e.g., MLflow, Weights & Biases, DVC, SageMaker, Vertex AI)Exposure to model safety, bias detection, explainability, and responsible AI practicesExperience with cloud platforms (AWS, Azure, GCP) for scalable AI deploymentsContributions to open source GenAI/ML projects or research publicationsAdditional Skills:Cloud Architectures, Cross Domain Knowledge, Design Thinking, Development Fundamentals, DevOps, Distributed Computing, Microservices Fluency, Full Stack Development, Release Management, Security-First Mindset, User Experience (UX)Interested candidates can apply at for more details.