- Company Name
- Genesis Molecular AI
- Job Title
- Head of Platform Engineering
- Job Description
-
**Job Title**
Head of Platform Engineering
**Role Summary**
Lead the design, implementation, and ongoing optimization of end‑to‑end AI platforms for training, inference, and data management at scale. Drive platform strategy, oversee infrastructure decisions, and build a high‑impact engineering team to support AI workloads in a dynamic, startup‑style environment.
**Expectations**
* Own end‑to‑end platform and infrastructure strategy for data ingestion, distributed training, evaluation, and production inference.
* Make trade‑off decisions between build vs. buy, performance, cost, reliability, and velocity.
* Lead, mentor, and grow a platform engineering team.
* Stay hands‑on and deeply involved in technical execution when required.
**Key Responsibilities**
* Architect and operate large‑scale AI workloads, ensuring reliability, scalability, and cost efficiency.
* Design and maintain data pipelines, storage solutions, and distributed computing environments (cloud and on‑prem).
* Evaluate, select, and integrate cloud, hardware, and machine‑learning platform components.
* Oversee lifecycle management of models, from training to production deployment and monitoring.
* Collaborate with data, ML, and product teams to define platform requirements and deliverables.
* Lead troubleshooting, capacity planning, and continuous improvement initiatives.
* Inspire a culture of performance engineering, automation, and rapid experimentation.
**Required Skills**
* 8+ years of experience designing and operating infrastructure for large‑scale AI training and inference.
* Deep knowledge of cloud platforms (AWS, GCP, Azure) and on‑prem hardware optimization.
* Proven experience with distributed training frameworks (e.g., PyTorch Lightning, Horovod, DeepSpeed).
* Strong systems thinking: ability to evaluate performance, cost, reliability, and development velocity trade‑offs.
* Leadership experience in a fast‑moving, startup‑like environment.
* Hands‑on proficiency in scripting, automation, and monitoring tools.
* Familiarity with container orchestration (Kubernetes) and CI/CD pipelines.
* Excellent communication and mentorship skills.
**Required Education & Certifications**
* Bachelor’s degree in Computer Science, Engineering, or related field. (M.S./Ph.D. preferred)
* Certifications in cloud platforms (e.g., AWS Certified Solutions Architect, GCP Professional Cloud Architect) are a plus.