LLM Engineer

Whitetable.ai

You will shape the future of technology and drive innovation in a collaborative environment.

Compensation:

INR 10M - 24M/year

+ Bonuses (up to 1% of base compensation)

Location:

Hybrid: DLF CyberHub (Gurugram, Haryana), DLF Cyber City, DLF Phase 2, Sector 24, Gurugram, Haryana, India

Mission of Whitetable.ai:

" Building AI APIs to enable ultra fast, optimal hiring."

What makes you a strong candidate:

• You are proficient in TensorFlow, Python, PyTorch, LLM evaluation.
• You have +3 years experience in Natural language processing (NLP), Machine learning, Artificial intelligence (AI).
• English - Conversational

Responsibilities and more:

Large Language Model (LLM) Engineer – ML & AI

Location: Full Time, In Office (Gurugram / Bengaluru).

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 you’ll have a front-row seat to shape the future of AI-driven Observability solutions.

What You’ll 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.

* Collaborate 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 (NumPy, Pandas, HuggingFace Transformers, PyTorch, LangChain).

What We’re Looking For:

* 3–5 years of experience in AI, Machine Learning, or NLP.

* 2+ years of hands-on experience building models from the ground up or fine-tuning large language models (multi-billion parameters).

* Deep expertise in LLM fine-tuning, distillation, model compression, and efficient inference techniques.

* Bachelor’s degree in Computer Science, AI/ML, or a related field; Master’s or PhD preferred.

* Proficiency in Python and libraries like Transformers, PyTorch, and 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 (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 bonus.

Our Values:

* Loyalty and long-term commitment.

* Opinionated yet open-minded.

* Passion for craft and innovation.

* Humility and integrity.

* Adaptability and self-sufficiency.

* Rapid iteration: build fast and break fast.

What You’ll Build:

You will be at the forefront of creating the next-generation Observability platform using advanced LLMs to reason over complex system signals. You will fine-tune large models, optimize them for production, and develop 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.