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 $200,000 to $450,000, supplemented by sign-on bonuses, relocation assistance, and full visa sponsorship for qualified candidates.
The Mission: Orchestrating the Future of Computational Biology
StaffRight Associates is sourcing an exclusive search for a Technical Program Lead of Machine Learning to join a world-class computational research collective in New York City. This role is situated at the bleeding edge of the In-Silico Revolution, where the objective is to bridge the gap between high-performance computing (HPC), advanced biophysics, and deep learning.
You will act as the structural glue between elite ML researchers and hardware engineers, driving the execution of projects that simulate molecular behavior at an atomic scale. The mission is clear: leverage proprietary supercomputing architectures and generative AI to accelerate the discovery of life-saving therapeutics and decode the fundamental mechanics of proteomic structures.
Core Technical Objectives
Orchestrate the end-to-end lifecycle of machine learning initiatives, focusing on the deployment of generative models for novel molecular synthesis and 3D structural prediction.
Synthesize complex research goals into actionable execution roadmaps, ensuring parity between ML model development and the physical constraints of biomolecular simulation.
Validate and manage the acquisition of massive, high-fidelity scientific datasets, serving as the primary technical liaison for external data vendors and strategic partners.
Formalize project frameworks for the application of Large Language Models (LLMs) within the domain of molecular science, specifically targeting PK/ADME property prediction.
Optimize cross-functional workflows between interdisciplinary teams of PhD-level researchers and systems architects to mitigate risk and ensure infrastructure scalability.
Deploy strategic risk-mitigation protocols for high-visibility projects, reporting directly to senior leadership on the technical health and velocity of the ML portfolio.
Candidate DNA
Architectural Philosophy: You possess a systems-thinking mindset, viewing ML not as a standalone tool, but as a component of a larger, integrated biophysical simulation pipeline.
Technical Depth: Extensive experience in Machine Learning and Computer Science, with a nuanced understanding of neural network architectures (Generative, Transformer-based, etc.) and their application to physical sciences.
Project Resilience: A proven track record of managing high-entropy, complex technical projects where the path from hypothesis to execution is non-linear.
Communication Precision: The ability to translate high-level mathematical concepts into operational directives for diverse engineering and research cohorts.
Academic & Research Pedigree
Foundational Rigor: A degree in Computer Science, Mathematics, Machine Learning, or a related quantitative field from a top-tier institution.
Theoretical Mastery: Deep familiarity with the mathematical underpinnings of ML and a first-principles understanding of computational modeling.
Interdisciplinary Fluency: While the core is technical, a strong intellectual affinity for biophysics, chemistry, or structural biology is highly prioritized.
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.
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