Scientific Software Engineer | Python-PyTorch

Location Note: This position is permanently based in New York City (Manhattan). While we are advertising in Boston to connect with top-tier technical talent, there is no remote or local hybrid option in Massachusetts. We are seeking elite researchers and engineers eager to advance world-class computational methods for drug discovery right from the heart of NYC’s biotech ecosystem.

Preface

The architectural integrity of global investment and technology research relies on the seamless convergence of Advanced Software Engineering and rigorous computational execution. Within this domain, where the synthesis of complex data and high-performance systems is the primary objective, the necessity for first-principles mastery extends beyond the laboratory and into the operational nucleus of the organization.

StaffRight Associates is seeking an elite professional to join the Computer Science team at a world-class firm dedicated to the advancement of computational excellence. This role demands a candidate who possesses the intellectual pedigree required to navigate the complex challenges of a research-intensive environment. By bridging specialized technical awareness with proactive problem-solving, the successful candidate will ensure the structural alignment of the firm’s strategic mission with its technical execution.

The Mission

StaffRight Associates is recruiting for a Software Developer to serve as a vital catalyst within a premier organization. The mission is to decouple systemic friction from analytical progress, allowing the firm’s leadership to maintain a singular focus on the acceleration of Molecular Simulation, Drug Discovery, and High-Performance ML Infrastructure. You will be tasked with the sophisticated management of Scientific Software Ecosystems and Distributed Data Pipelines, transforming abstract organizational needs into formalized, actionable results. This role requires a high degree of technical literacy to effectively support a team leveraging proprietary architectures and sophisticated algorithms to revolutionize Computational Drug Discovery and Molecular Dynamics.

Core Technical Objectives

• Orchestrate Systemic Workflows: Formalize, deploy, and support complex software tools and high-stakes technical workflows to ensure continuous operational flow for the computational chemistry, biology, and machine learning research teams.

• Synthesize Complex Data: Architect and engineer robust data pipelines and tools capable of managing large-scale, multidimensional scientific datasets, distilling multifaceted information into coherent frameworks.

• Optimize Operational Frameworks: Install, upgrade, and troubleshoot intricate software systems and ML training pipelines (including distributed/parallel training and LLM deployment) with meticulous attention to detail and systemic accuracy.

• Engineer Multi-Project Solutions: Independently manage a diverse portfolio of concurrent projects—ranging from scripting cheminformatics workflows to building third-party integrations—applying a proactive Goal-Execution-Mapping (GEM) approach to solve emergent bottlenecks.

• Facilitate Elite Communication: Serve as a discreet and articulate interface between the computer science committee, machine learning engineers, and laboratory stakeholders, maintaining the highest standards of professional integrity.

Candidate DNA

• Architectural Philosophy: A mindset rooted in efficiency and resilience, with the ability to navigate a hybrid, high-pressure environment without supervision. Comfortable with a schedule requiring in-office collaboration Tuesday through Thursday.

• Resourceful Problem-Solving: A proven track record of autonomous execution, demonstrating a strong interest in improving computing environments for end-users and anticipating systemic bottlenecks before they impact the broader research workflow.

• Communication Precision: Exceptional interpersonal skills characterized by clarity, discretion, and the ability to interact and collaborate with elite scientific, machine learning, and business minds.

• Functional Versatility: A generalist mindset capable of pivoting fluidly between automated Python scripting, low-level performance optimization, and cutting-edge generative/agentic AI experimentation within a high-performance ecosystem.

Academic & Research Pedigree

• Educational Foundation: An advanced degree is preferred, ideally within a STEM discipline (Computer Science, Physics, Chemistry, or related fields) that provides a foundation for understanding complex computational modeling.

• Domain Expertise: Prior professional engagement within high-performance computing (HPC), GPU clusters, Linux/UNIX environments, or advanced technology sectors. Experience with ML/AI frameworks ($PyTorch$, $MLflow$, $vLLM$, $SGLang$) or computational drug discovery is highly advantageous.

• Quantitative & Computational Literacy: Comfort with the mathematical and operational rigor inherent in a firm focused on supercomputing ($C++$ proficiency) and high-speed molecular data processing. Intellectual curiosity and a track record of concrete achievement outweigh specific niche exposure.

Compensation & Environment

• Financial Framework: Expected annual base salary of $250,000 – $600,000, structured alongside competitive variable compensation (sign-on and year-end bonuses) and premium benefits including relocation and immigration assistance.

• Work Structure: A modern hybrid ecosystem consisting of 3 days in-office (Tuesday–Thursday) and 2 optional remote days (Monday/Friday) 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, and your approach to system resilience to the most sophisticated STEM challenges in the industry.

When you partner with us, you are engaging with an elite 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.