Machine Learning - Engineer | Research

This role is based in New York, NY, offering a hybrid work model (3 in-office & 2 remote) and an elite compensation package ranging from $300,000 to $800,000, supplemented by sign-on bonuses, relocation assistance for qualified candidates.

The Mission

StaffRight Associates is spearheading an exclusive search for elite Machine Learning - Engineer & Researcher  to join a premier interdisciplinary research collective. This role is situated at the critical nexus of computational biophysics and advanced AI, where the objective is to transcend traditional drug discovery limitations through systemic innovation. You will be tasked with architecting and deploying sophisticated deep learning models that interface with high-performance computing ecosystems to simulate and manipulate the behavior of complex biological macromolecules. The mission is nothing less than the digital formalization of molecular dynamics to accelerate life-saving scientific breakthroughs.

Core Technical Objectives

• Synthesize novel deep learning architectures to enhance the fidelity of quantum chemical models and biomolecular simulations.

• Orchestrate the development of generative models designed to produce optimized molecular structures for therapeutic intervention.

• Engineer high-performance Python frameworks to bridge the gap between massive datasets and specialized supercomputing hardware.

• Validate the structural alignment of neural network outputs against empirical biophysical data and structural biology benchmarks.

• Formalize new methodologies for reinforcement learning and graph-based networks to navigate the immense chemical space of drug discovery.

• Collaborate within a high-stakes, cross-functional environment, integrating insights from theoretical chemistry and computer science to drive systemic research impact.

Candidate DNA

• Architectural Philosophy: A first-principles thinker who views machine learning not as a black box, but as a precise instrument for physical and biological inquiry.

• Technical Depth: Mastery of advanced deep learning paradigms, including but not limited to Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Graph Neural Networks (GNNs), and Deep Reinforcement Learning.

• Computational Fluency: Expert-level command of Python, with a demonstrated ability to write clean, scalable, and performance-optimized code. Exposure to additional low-level or specialized programming environments is highly valued.

• Domain Versatility: While direct experience in cheminformatics, molecular dynamics, or quantum chemistry is preferred, we prioritize candidates with the intellectual agility to apply ML innovations to complex, multi-dimensional scientific problems.

• Innovation Pedigree: A documented history of pushing the boundaries of what is possible in AI, whether in a high-growth startup, an elite tech lab, or a world-class academic setting.

Academic & Research Pedigree

• Mathematical Rigor: A background rooted in the mathematical foundations of machine learning, demonstrating a deep understanding of optimization, linear algebra, and statistical mechanics.

• Educational Excellence: An advanced degree (PhD preferred) from a top-tier global institution in Computer Science, Physics, Computational Chemistry, or a related quantitative field.

• Proven Innovation: A track record of high-impact research, peer-reviewed publications, or significant technical contributions that demonstrate a Goal-Execution-Mapping approach to solving non-trivial problems.

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.