LinkedIn Summary Examples for AI Researchers

After 5 years fine-tuning transformers at a mid-sized AI firm in Seattle, I'm hunting senior researcher spots at AGI-focused labs. My latest: a PEFT method for LLMs that slashed VRAM use by 60% on A100s, detailed in my arXiv preprint (150+ citations already). Deployed it to personalize recommendations for 500k users.

Skilled in PyTorch, JAX, and Weights & Biases for scalable training. Tackled federated learning challenges in privacy-sensitive domains like healthcare. Co-authored 2 ICML papers on continual learning to fight forgetting.

Open to roles blending research and engineering. Love turning theory into production magic. Let's chat if you're building safe, scalable AI. GitHub: github.com/myhandle | arXiv: arxiv.org/user/me

PhD in ML from Stanford, now wrapping a postdoc at UC Berkeley on multimodal foundation models. Built a CLIP variant outperforming OpenAI's by 8% on zero-shot tasks, open-sourced with 2k stars.

Expertise spans vision-language pretraining, diffusion models, and RLHF. Used Ray Tune for hyperparam sweeps across 100+ GPUs. Previous internship at Meta AI optimized FlashAttention for long-context training.

Targeting research scientist roles at places like Anthropic or DeepMind. Eager to contribute to alignment and scaling. Drop me a note on multi-agent systems or efficient inference.

15+ years in AI, from early neural nets to today's LLMs. Principal Researcher at FAIR, led teams on self-supervised learning that powered Llama models (500k+ citations aggregate).

Key contribs: Pioneered sparse MoE architectures reducing inference costs 4x, ICML best paper 2022. Maintain active blog on scaling laws, Substack 10k subs. Mentor 20+ PhDs now at top labs.

Consult for VCs on AI startups. Speak at NeurIPS, CVPR. Current focus: Robustness in generative models against adversarial attacks.

Connect if you're in AI ethics, hardware-software co-design, or want recs on JAX vs PyTorch for prod.

Ex-Google Brain, now independent AI researcher with 300+ pubs. Specialized in reinforcement learning for robotics. My PPO variant with hindsight experience replay beat baselines by 30% on MuJoCo, Hugging Face trending.

Developed Gymnasium envs used in 50k+ projects. Co-founded RLlib contrib group. Patents on sim-to-real transfer deployed in warehouse bots.

Writing book on scalable RL. Available for advising, keynotes. Thoughts on arXiv daily. Let's collaborate on real-world agents.

Over a decade directing AI labs, from startups to Big Tech. Drove Rosetta model at xAI, handling 10B params on consumer GPUs via custom quantization.

20 NeurIPS/ICML papers, h-index 45. Optimized throughput 5x with DeepSpeed. Advise on AI infra for Series A firms.

Passions: Emergent abilities in scaling, neuro-symbolic hybrids. Ping for co-authorship or talent intros.

AI researcher by day, sci-fi reader by night. Currently hacking on agentic workflows at a Boston startup. Just shipped a LangChain extension for tool-use that handles 95% fewer hallucinations, 5k downloads.

Came from physics PhD, pivoted to ML after grokking transformers. Favorites: Building RAG pipelines that actually work, and debating AGI timelines over coffee.

Not chasing FAANG, but open to fun projects in embodied AI or music gen. GitHub's where the real story is. Say hi if you hate prompt engineering as much as I do.

Hey, I'm Alex. Spend my time making computers think more like humans, less like calculators. Last year, fine-tuned Mistral-7B for code gen, beating GPT-4 on HumanEval for niche langs.

Love PyTorch, hate debugging OOM errors. Co-run a meetup on federated learning. Side hustle: AI art with Stable Diffusion tweaks.

Always down for chats on ethical AI or beer. Links below.

Deployed 7 production ML models serving 2M+ daily users. Reduced latency 70% via distilled BERT variants at e-commerce giant.

Led vision team: YOLOv8 fine-tune hit 92% mAP on custom dataset, cut false positives 40%. 150k GitHub stars across repos.

PhD thesis on GNNs scaled to 1M nodes, NeurIPS 2023. Now at AI consultancy optimizing LLMs for edge.

Expert: TensorFlow, ONNX, Triton Inference. Seeking principal roles. Connect.

My diffusion model repo: 300k downloads, 4.5k stars. Achieved SOTA FID 2.1 on FFHQ, trained on single RTX 4090.

Previously: RLHF pipeline for chatbots, +25% win rate vs GPT-3.5 in evals. Scaled to 100k params/hr on TPUv4 pods.

ICLR spotlight paper on efficient sampling. Tools: ComfyUI, Diffusers lib.

Open for partnerships in gen AI.

Saved client $2M/year by compressing LLMs 8x with QLoRA, no perf drop. Models now run on phones.

Track record: 12 papers, 1k cites. Boosted throughput 3x in recsys with xFormers.

From academia to prod: Proficient in vLLM, Haystack. Hiring? I'm your scaling guy.