Latest AI JobsBrowse Jobs
pointfive logo

Head of LLM Research

pointfiveTel AvivEngineering
Apply on company site
Salary
Not listed
Job type
Full-time
Work mode
Remote
Experience
Lead
Posted
17 Sept 2026
Status
Open · checked 7d ago

About this role

Located in Tel Aviv, the Head of LLM Research position at PointFive involves leading the research agenda for artificial intelligence models, evaluation frameworks, and deployment efficiency. This role suits an experienced researcher who wants to directly impact infrastructure products and shape the intelligence behind developer-focused AI tools.

Role Overview

PointFive is seeking an AI researcher to investigate model behavior, evaluation metrics, and efficiency across real engineering workloads. The position operates within PointFive Labs, the company's research arm, and involves collaborating closely with engineering and product teams. The role requires building and leading a small research team over time while translating research results into production capabilities.

Key Responsibilities

Define and lead the LLM research agenda across model evaluation, inference optimization, local models, routing, and model adaptation.
Continuously evaluate frontier and open-weight models across real-world software engineering and agentic workloads.
Design rigorous evaluation frameworks for model quality, reasoning, tool use, code generation, and agent behavior.
Research model efficiency techniques including quantization, distillation, speculative decoding, prefix caching, KV-cache optimization, batching, and context management.
Investigate when smaller or locally deployed models can replace expensive frontier models without materially degrading task quality.
Research and benchmark local inference stacks and study inference performance across heterogeneous hardware configurations.
Develop model-routing strategies that optimize across quality, latency, cost, privacy, context size, and hardware availability.
Build internal research infrastructure for reproducible model experiments, benchmarking, dataset management, and evaluation.
Collaborate closely with engineering and product teams to translate research results into production capabilities and build a small research team over time.

Requirements

Deep understanding of modern large language models and transformer-based architectures.
Strong hands-on experience evaluating and experimenting with both frontier and open-weight models.
Strong understanding of inference behavior, including prefill, decoding, KV caches, context windows, batching, memory usage, and token generation performance.
Experience with model optimization techniques such as quantization, distillation, LoRA, fine-tuning, or model compression.
Strong experimental mindset to formulate hypotheses, design controlled experiments, and draw meaningful conclusions from noisy results.
Experience building evaluation frameworks for LLM quality and behavior.
Strong Python proficiency and familiarity with the modern machine learning ecosystem.
Ability to read, understand, and reproduce ideas from current machine learning research papers.
Comfort working with ambiguous research problems lacking established best practices.
Strong ability to bridge research and production viability.

Nice to Have

Experience with open-weight models such as Llama, Qwen, DeepSeek, Mistral, Gemma, GLM, or similar families.
Experience with frontier model APIs including OpenAI, Anthropic, Google, and other leading providers.
Experience with inference frameworks such as vLLM, SGLang, llama.cpp, MLX, TensorRT-LLM, Ollama, or ONNX Runtime.
Deep understanding of quantization techniques including FP8, INT8, INT4, AWQ, GPTQ, and GGUF.
Experience with GPU performance optimization, CUDA, Metal, ROCm, or DirectML.
Familiarity with distributed inference, multi-GPU serving, model routing, mixture-of-model systems, cascades, or adaptive inference.
Experience with reinforcement learning, preference optimization, DPO, GRPO, agentic systems, coding agents, and tool-use models.
Research publications or meaningful contributions to open-source machine learning projects, and experience leading a small applied research team.

Skills and Tools

Python
llama.cpp
MLX
vLLM
SGLang
ONNX Runtime
Ollama
TensorRT-LLM
CUDA
Metal
ROCm
DirectML

About the Company

PointFive helps Fortune 500 companies identify and reduce infrastructure and AI costs, pioneering DeepWaste across cloud and data platforms and TokenShift for AI token spend. Backed by $96 million in funding, including a Series B led by Accel, the company maintains its engineering operations in Tel Aviv and its go-to-market team in North America. PointFive has been recognized by CRN, Forbes Israel, and Redpoint as a leading infrastructure and cloud startup.

How to Apply

Candidates should apply on the official company careers page.

Skills and tech stack

Pythonllama.cppMLXvLLMSGLangONNX RuntimeOllamaTensorRT-LLMCUDAMetalROCmDirectMLFP8INT8INT4AWQGPTQGGUFPyTorchLLMAWSReinforcement LearningFine-tuningHugging Face

Questions candidates ask

Where is the Head of LLM Research role located?

The engineering team and this role are based in Tel Aviv.

What kind of company is PointFive?

PointFive builds infrastructure for enterprise cost visibility and AI token spend, helping Fortune 500 companies manage cloud and AI costs.

Will this role involve managing people?

Yes, the position involves building and leading a small, exceptional LLM research team over time.

What technical background is required for the position?

The role requires a deep understanding of modern large language models, transformer-based architectures, inference behavior, model optimization techniques, and strong Python proficiency.

Are there specific inference frameworks mentioned as nice-to-have experience?

Yes, nice-to-have frameworks include vLLM, SGLang, llama.cpp, MLX, TensorRT-LLM, Ollama, and ONNX Runtime.

Ready to apply?

The application is on the official pointfive careers page.

Apply on company site