LLM Engineer - Machine Learning

Location : Full Time, In Office (Gurugram )

About Us :

We are an early-stage startup disrupting the Observability domain with Generative AI and Machine Learning. Our team includes experienced entrepreneurs and engineers who have built multiple billion-dollar products from scratch. As a well-funded US-based company backed by top-tier VCs, we have offices in the US, India, and Europe. Join us in our fast-paced environment where youll have a front-row seat to shape the future of AI-driven Observability Youll Work On :

• Train and fine-tune Large Language Models (LLMs) for tasks related to reasoning, diagnostics, and observability.
• Build efficient LLM distillation and quantization pipelines to optimize large models for real-time performance.
• Design LLM evaluation frameworks to benchmark model accuracy, reasoning capabilities, and production-readiness.
• Develop prompt engineering strategies and instruction tuning datasets tailored to observability and monitoring use cases.
• Create LLM Ops workflows to manage model lifecycle - including versioning, deployment, and monitoring.
• Integrate LLMs into an intelligent root cause analysis system, powered by causal reasoning, time series data, and anomaly detection.
• Work closely with ML engineers and product teams to translate research into production-grade features.
• Build tools to simulate, test, and evaluate LLM agents for diagnostic and monitoring applications.
• Handle large-scale datasets using Python and its ML ecosystem (e.g., NumPy, Pandas, HuggingFace Transformers, PyTorch, Were Looking For :
• 5+ years of experience in AI, Machine Learning, NLP
• 2+ years of hands-on experience building models from ground up or fine-tuning large language models (mutil-billion parameters)
• Deep expertise in LLM fine-tuning, distillation, model compression, and efficient inference techniques.
• Bachelors degree in Computer Science, AI / ML, or related field. Masters or PhD preferred.
• Proficiency in Python and libraries like Transformers, PyTorch, TensorFlow
• Experience building LLM training datasets, synthetic data generators, and prompt tuning frameworks.
• Familiarity with LLM evaluation, including factuality, hallucination detection, and functional correctness.
• Strong understanding of LLM Ops principles (e.g., model tracking, deployment pipelines, performance monitoring).
• Prior experience with time series analysis, anomaly detection, or causal inference is a plus.
• Background in LLM agent development, multi-agent coordination, or autonomous reasoning systems is a strong plus.
• Experience in observability, monitoring, or devops tooling is a big Values :
• Loyalty & Long-term Commitment - We invest in people who invest in us.
• Opinionated yet Open-Minded - We value strong perspectives but encourage constructive discussions.
• Passion - We seek individuals who are passionate about their craft.
• Humility & Integrity - Honest, transparent, and accountable team members are key.
• Adaptability & Self-Sufficiency - Ability to thrive in a fast-paced and evolving environment.
• Build Fast and Break Fast - We believe in rapid iteration and learning from Youll Build :

You will be at the forefront of building the next-generation Observability platform using advanced LLMs to reason over complex system signals. Youll work on fine-tuning large models, optimizing them for production, and creating frameworks to evaluate and deploy intelligent AI agents that assist in diagnostics and monitoring. This is a rare opportunity to work with a veteran founding team and shape the future of AI-driven infrastructure.

ref : hirist.tech)