VPP-– LLM Scientist - Remote

We are seeking a LLM Scientist with expertise in natural language processing (NLP), large language models (LLMs), and deep learning. The ideal candidate will have strong experience in fine-tuning and adapting transformer-based models, optimizing Retrieval-Augmented Generation (RAG) pipelines, and deploying scalable AI-driven solutions. You will be responsible for designing, training, and evaluating language models, working closely with engineers to integrate them into production systems.

Department:

AI, Insights, & Solutions

Project Location(s):

United States - Remote

Job Type:

Employee

Education:

Bachelor's

You will collaborate closely with Data Engineers, enhancing the quality of data and the efficiency of data pipelines. You will also contribute to a team culture that values mentorship and knowledge sharing by translating complex research into actionable tasks for the team.

• Extensive experience with PyTorch and the Hugging Face ecosystem (Transformers, PEFT, Accelerate)
• Proven track record of fine-tuning models, with a deep understanding of attention mechanisms, positional embeddings, and transformer architectures
• Hands‑on experience with vector databases (Pinecone, Milvus) and familiarity with the mathematics behind similarity search and embedding models
• Proficiency in Python, along with familiarity in containerization (Docker) and cloud‑scale AI training (AWS Sage Maker/GCP Vertex AI)
• Ability to analyze model failures, hypothesize root causes, and systematically test solutions

• Design and execute experiments by conducting ablation studies on various prompt strategies, tokenization methods, and fine‑tuning hyperparameters
• Own model decisions regarding the selection of foundation models for specific tasks and the acceptable trade‑offs between latency and accuracy
• Architect data pipelines in collaboration with Data Engineers to curate high‑quality synthetic data and improve model training efficiency
• Solve complex “hallucination” problems by serving as the final escalation point for enhancing model factuality and designing logic for retrievers and re‑rankers
• Mentor the team by translating the latest research papers into actionable engineering tickets

• Advanced Degree: A Master’s or PhD in Computer Science, Math, or a related field with a focus on NLP
• Multi‑Modal
  
  Experience:
  
  Familiarity with Vision‑Language Models (VLM) or audio‑to‑text integration
• Reinforcement Learning:
  Experience with RLHF (Reinforcement Learning from Human Feedback) or DPO (Direct Preference Optimization)
• Open Source Presence: A portfolio of public Git Hub repos, Hugging Face models, or published papers in the GenAI space
• Hardware Knowledge:
  Deep understanding of NVIDIA GPU architectures (H100/A100) and CUDA kernels to maximize hardware utilization

Vekend is a people‑first organization focused on developing thoughtful products and services that create meaningful impact for our customers and communities. We are committed to fostering a collaborative, respectful, and inclusive work environment where employees are empowered to take ownership of their work, contribute ideas, and grow professionally. We strive to support flexibility and work‑life balance while maintaining high standards of performance and accountability.

For all locations, the good‑faith, reasonable annualized full‑time compensation for this role will be determined based on competitive market data and may vary depending on geographic location, job‑related knowledge, skills, experience, education, and other business considerations. Specific compensation details will be discussed during the interview process. Vekend offers a comprehensive benefits and wellness package designed to support employees’ overall well‑being, financial security, and professional growth.

Eligibility and coverage are subject to the terms of the applicable benefit plans and company policies. Eligible employees have access to medical, dental, and vision insurance with company contributions toward premiums, a 401(k) retirement plan with company matching, and Paid Time Off that begins accruing on the first day of employment. We also support flexible work arrangements and opportunities for professional growth.

Benefits eligibility, coverage, and company contributions are subject to the terms of the applicable plan documents and may be modified at the company’s discretion.