- Company Name
- Loop Recruitment
- Job Title
- Artificial Intelligence Engineer
- Job Description
-
**Job Title:** Artificial Intelligence Engineer
**Role Summary:**
Design, build, and maintain large‑scale machine learning systems that enable an autonomous AI‑driven material discovery platform. Work alongside chemists and material scientists to deploy data‑centric pipelines, simulation tools, and AI algorithms that scale across HPC clusters and cloud environments. Balance engineering rigor with cutting‑edge research to accelerate the closed‑loop discovery of novel physical materials.
**Expectations:**
* Deliver production‑ready ML infrastructure within a fast‑paced, high‑impact research setting.
* Own end‑to‑end delivery of data pipelines, model training, inference, and deployment workflows.
* Collaborate tightly with scientific teams to evaluate and iterate on novel algorithms that directly influence physical experimentation.
* Maintain performance, scalability, reproducibility, and data stewardship standards across distributed systems.
* Communicate design choices, trade‑offs, and results to both technical and non‑technical stakeholders.
**Key Responsibilities:**
* Architecture and implementation of scalable ML pipelines for training, inference, and continuous integration.
* Development of tooling and infrastructure that accelerate AI‑driven simulation, high‑throughput experimentation, and data management.
* Deployment and evaluation of state‑of‑the‑art ML models (e.g., deep learning, graph neural networks) in collaboration with domain experts.
* Optimization of compute performance on HPC clusters and cloud platforms, ensuring reproducibility and efficient resource usage.
* Curate and maintain data pipelines, evaluation frameworks, and metadata services to support rigorous scientific assessment.
* Mentor and review code from teammates, enforce best practices for version control, testing, and documentation.
**Required Skills:**
* 2+ years of experience building and deploying robust ML systems in research‑driven environments.
* Proficient in Python, PyTorch or equivalent deep‑learning frameworks, and Linux-based system administration.
* Strong command of Git, automated testing, CI/CD, and containerization (Docker/Kubernetes).
* Experience with HPC clusters, cloud compute services (AWS/GCP/Azure), and distributed training techniques.
* Knowledge of data engineering concepts: pipelines, data lakes, schema management, and metadata indexing.
* Ability to translate scientific requirements into scalable software solutions and communicate across disciplines.
**Required Education & Certifications:**
* Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Physics, Materials Science, or related STEM field (or equivalent practical experience).
* Technical certifications (e.g., AWS Certified Machine Learning, GCP Professional Data Engineer) are a plus but not mandatory.