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Software Engineer - Machine Learning Infrastructure

On-site Full-time

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Experience Level

Experience

Qualifications

Proven experience in software engineering, particularly with a focus on ML infrastructure. Strong knowledge of distributed systems and cloud computing. Experience with GPU performance optimization. Ability to work collaboratively in cross-functional teams. A passion for advancing AI in the field of biochemistry.

About the job

About Our Team

At Genesis Molecular AI, we are a dedicated group of innovative drug hunters, deep learning researchers, and skilled software engineers, all striving to revolutionize biochemistry. Our mission is to harness the power of AI to discover and develop groundbreaking therapies for patients dealing with severe disorders.

Our team is engaged in pioneering the development of foundational models for small molecule drug discovery, conducting essential research at the intersection of machine learning, physics, and computational chemistry. We engineer robust software systems that support extensive simulations and facilitate the training of generative and predictive AI models capable of learning from diverse molecular data, leveraging a powerful cluster of thousands of GPUs and tens of thousands of CPUs.

About the Position

We are in search of talented ML Infrastructure Engineers who are ready to take the lead in advancing our machine learning research agenda for generative modeling of molecular systems, a key component of our mission.

In this role, you will spearhead the rapid evolution of our AI platform and infrastructure, unlocking unprecedented levels of performance, efficiency, and scalability. You will be responsible for constructing massively distributed training and inference pipelines, core MLOps tools and frameworks, as well as optimizing GPU operations to enhance the speed of ML models.

Genesis fosters a collaborative and cross-functional environment, offering the opportunity to work closely with our exceptional engineers, researchers, and scientists.

Your Responsibilities

  • Lead engineering initiatives aimed at the continuous enhancement of our AI platform, focusing on the rapid development of scalable and resilient distributed infrastructure for ML training, inference, and evaluation.

  • Facilitate model training and deployment across multiple clusters and cloud environments, with an emphasis on optimizing throughput and cost-effectiveness.

  • Maximize the efficiency of ML models and various workloads regarding latency, throughput, and memory usage (e.g., through GPU performance engineering), pushing the limits of current hardware capabilities.

  • Contribute to the long-term strategic vision for Genesis’ infrastructure platform.

Qualifications

We are looking for engineers with a strong foundation in software development and a passion for machine learning, particularly in the context of infrastructure and distributed systems.

About Genesis Molecular AI

Genesis Molecular AI is at the forefront of AI innovation in drug discovery, utilizing advanced machine learning techniques to develop transformative therapies for patients facing severe conditions. Our team comprises some of the brightest minds in drug hunting, deep learning, and software engineering, all dedicated to making a significant impact in the healthcare space.

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