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Senior LLM Research Scientist - Engineer

Jobs via Dice
Boston, MA Full Time
POSTED ON 5/26/2026 CLOSED ON 6/20/2026

What are the responsibilities and job description for the Senior LLM Research Scientist - Engineer position at Jobs via Dice?

Dice is the leading career destination for tech experts at every stage of their careers. Our client, StaffRight Associates, LLC, is seeking the following. Apply via Dice today!

  • Location Note: While this role is being advertised in Boston, Massachusetts to reach the top technical talent, the position is permanently based in New York City. We are looking for researchers and engineers ready to apply world-class computational methods to drug discovery and biomolecular simulation in the heart of Manhattan’s growing biotech ecosystem.

Preface

The convergence of Computational Biophysics and Foundational Machine Learning represents the current frontier of therapeutic discovery. This mandate requires an elite practitioner possessing a Ph.D. or equivalent Master’s-level rigor, capable of applying first-principles mastery to the architectural challenges of Large Language Models (LLMs). The successful candidate will transition beyond standard NLP, utilizing deep technical intuition to bridge the gap between high-dimensional transformer architectures and the stochastic complexities of molecular dynamics. This is a forensic search for a researcher-engineer who views code as a vehicle for scientific proof and system optimization as a prerequisite for breakthrough discovery.

The Mission

StaffRight Associates is orchestrating an exclusive search for foundational LLM Researchers and Engineers to join an interdisciplinary collective dedicated to the structural alignment of generative AI and molecular science. The mission is to architect and deploy large-scale, multimodal models that transcend text, capturing the intricate spatial and temporal behaviors of biological systems at atomic resolution.

By leveraging one of the world''''''''s most advanced specialized computing environments, the incumbent will decouple complex biochemical problems through the lens of high-performance distributed training and innovative post-training methodologies.

Core Technical Objectives

  • Orchestrate large-scale distributed training and inference workflows, maximizing throughput and system efficiency on proprietary, high-performance computing (HPC) clusters.
  • Synthesize robust data ingestion and preprocessing pipelines for massive-scale pre-training, ensuring data integrity across parallelized environments.
  • Formalize advanced post-training protocols, including Reinforcement Learning (RLHF/RLAIF), contrastive learning, and precision instruction tuning to refine model utility.
  • Engineer multimodal architectures that integrate non-linguistic data structures, specifically molecular graphs, 3D atomic coordinates, and sequential time-series data.
  • Validate model performance against complex scientific benchmarks, ensuring that generative outputs align with physical and chemical constraints.

Candidate DNA

  • Architectural Philosophy: A deep-seated understanding of transformer-based architectures and the mathematical underpinnings of attention mechanisms.
  • System Resilience: Proven ability to manage the volatility of large-scale training runs, possessing the debugging intuition required for massive parameter sets.
  • Technological Versatility: A background characterized by intellectual agility—transitioning seamlessly between high-level Pythonic implementation and low-level optimization.
  • Scientific Curiosity: While prior experience in drug discovery is not a prerequisite, a profound interest in applying ML to the physical sciences is essential.

Academic & Research Pedigree

  • Advanced Degree: Ph.D. or Master’s in Computer Science, Physics, Mathematics, or a related quantitative STEM field.
  • Technical Stack: Expert-level command of Python; familiarity with C /CUDA or specialized hardware acceleration is highly advantageous.
  • Proven Impact: A track record of high-caliber contributions, evidenced by peer-reviewed publications at top-tier venues (e.g., NeurIPS, ICML, ICLR) or the delivery of high-impact proprietary models at leading AI research labs.

Compensation & Environment

  • Base Salary Range: $300,000 – $800,000 (commensurate with research impact and technical depth).
  • Incentive Structure: Comprehensive package including sign-on bonuses, performance-based year-end equity/bonuses, and full relocation/immigration support.
  • Operational Model: A high-collaboration hybrid framework (3 days in-office, 2 days remote) based in New York City.

Partnering with StaffRight Associates: At StaffRight Associates, we operate at the intersection of technical synthesis and structural alignment. We don’t just match resumes to keywords; we map your engineering DNA, your architectural philosophy, your approach to system resilience, and your Goal-Execution-Mapping, to the most sophisticated STEM challenges in the industry.

When you partner with us, you are engaging with a team that speaks your language and understands the nuances of high-stakes innovation. We are committed to placing elite talent where their technical contributions drive systemic impact.

Salary : $300,000 - $800,000

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