Senior Machine Learning Engineer

Core-LLM Platform Team Overview

Join our pioneering Core-LLM platform team, where we are dedicated to pushing the boundaries of Generative AI. Our focus is on developing robust, scalable, and safe machine learning models, including Large Language Models (LLMs), Small Language Models (SLMs), Large Reasoning Models (LRMs), and Small Reasoning Models (SRMs) that power ServiceNow's cutting-edge products and features. As a Senior Machine Learning Engineer in Hyderabad, India, you will play a pivotal role in shaping the future of our AI capabilities, ensuring the ethical and effective deployment of our technology.

Key Responsibilities

• Design, develop, and evaluate end-to-end machine learning solutions, with a strong emphasis on large language models (LLMs), integrating engineering rigor with research depth.
• Lead the development of Proofs of Concept (PoCs) and applied research prototypes to explore novel AI capabilities, model interpretability, and safety strategies.
• Conduct cutting-edge experiments to assess model behavior, generalization, and fairness across diverse datasets and use cases.
• Generate and curate synthetic and real-world datasets to optimize model robustness, reliability, and performance.
• Fine-tune and deploy large-scale models, utilizing techniques such as prompt engineering, few-shot learning, and retrieval-augmented generation.
• Collaborate cross-functionally with product, research, and engineering teams to publish white papers, present at conferences, and contribute to open-source or peer-reviewed ML/AI research.
• Define and implement rigorous evaluation protocols, including human-in-the-loop testing, bias detection, and safety metrics.
• Develop CI/CD pipelines and containerized workflows for scalable training, evaluation, and deployment of ML solutions in production environments.
• Identify risks in AI applications and contribute to responsible AI initiatives, focusing on transparency, robustness, and compliance frameworks.

Qualifications

• Experience with AI Productivity tools such as Cursor or Windsurf is a plus.
• Hands-on experience with methods for training and fine-tuning large language models, including distillation, supervised fine-tuning, and policy optimization.
• Minimum of 5 years of experience in machine learning, deep learning, or data science, with a proven track record of applied research or experimentation.
• Strong proficiency in Python and ML frameworks like PyTorch, TensorFlow, HuggingFace Transformers, and NumPy.
• Practical experience with prompt engineering, model training, evaluation, and optimization for LLMs or foundation models.
• Demonstrated experience in applied research, academic publication, technical blogging, or contributions to open-source ML projects.
• Familiarity with data-centric AI workflows, including synthetic data generation, labeling strategies, and dataset versioning tools.
• Deep understanding of AI/ML evaluation strategies, model robustness techniques, and responsible AI practices.
• Practical experience deploying models using inference platforms such as Triton or ONNX in production environments.
• Experience working with MLOps stacks including CI/CD, experiment tracking (e.g., MLflow), Docker, Kubernetes, and distributed training frameworks.
• Excellent communication skills, with the ability to articulate complex ML concepts to non-technical stakeholders and contribute to scientific documentation.

Location: Hyderabad, India