Machine Learning - Engineer & Researcher

***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

This search targets the intersection of Computational Biophysics and Foundational Machine Learning, necessitating a candidate who possesses an elite academic pedigree, typically characterized by a Ph.D. in Computer Science, Physics, or a related quantitative field. The role demands a first-principles mastery of deep learning architectures to navigate the high-dimensional complexity of molecular space. To succeed, the researcher must bridge abstract algorithmic theory with practical biochemical application, synthesizing novel neural frameworks that can effectively model and predict the stochastic behavior of biological macromolecules. This mandate requires an individual capable of translating rigorous mathematical proofs into scalable, high-performance computational models that drive systemic breakthroughs in therapeutic discovery.

The Mission

StaffRight Associates is recruiting to identify a ''''visionary'''' Machine Learning - Engineer | Researcher to join an elite interdisciplinary collective in New York City. The mission is to architect and deploy sophisticated ML frameworks that redefine the boundaries of biomolecular simulation and drug design. By integrating advanced deep learning techniques with massive-scale computational power, the successful incumbent will play a pivotal role in transforming the predictive accuracy of molecular dynamics and accelerating the evolution of medicinal chemistry through systemic algorithmic innovation.

Core Technical Objectives

• Synthesize novel deep learning architectures—including graph neural networks, generative models, and reinforcement learning frameworks—to decode complex biophysical interactions.

• Engineer high-performance Python-based environments to facilitate the training and deployment of models on bespoke, ultra-high-speed supercomputing infrastructure.

• Validate the efficacy of neural networks in enhancing the precision of quantum chemical models and structural biology simulations.

• Optimize generative algorithms to autonomously design and refine molecular structures with high therapeutic potential.

• Decouple complex biological datasets into actionable features, leveraging transfer learning and deep belief networks to inform the drug discovery pipeline.

• Orchestrate collaborative research efforts alongside chemists and biologists to ensure mathematical models align with empirical scientific reality.

Candidate DNA

• Architectural Philosophy: A deep-seated commitment to developing robust, scalable, and innovative deep learning solutions for multi-dimensional scientific challenges.

• Technical Depth: Mastery of the deep learning stack, including but not limited to CNNs, RNNs, Boltzmann machines, and graph-based learning.

• Algorithmic Versatility: The ability to pivot between various domains such as cheminformatics, medicinal chemistry, and quantum mechanics with intellectual curiosity and technical rigor.

• Systemic Impact: A proven track record of pioneering ML research or engineering that has resulted in peer-reviewed publications or significant industry advancements.

• Coding Proficiency: Expert-level Python capabilities, with a preference for candidates who exhibit a sophisticated understanding of software engineering principles and performance optimization.

Academic & Research Pedigree

• Educational Foundation: An advanced degree (Ph.D. or Master’s) in a STEM discipline with a heavy emphasis on computational methods, mathematics, or theoretical physics.

• Research Excellence: Demonstrated history of innovation in machine learning, evidenced by a portfolio of work that showcases an ability to solve non-trivial, open-ended scientific problems.

• Mathematical Rigor: A first-principles understanding of the statistical and mathematical underpinnings of modern AI/ML.

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