NanoCure AI R&D Foundation for Cancers and Diseases · 1 hour ago
Machine Learning Engineer (Early Career / New Graduate)
United States
Full-time
Remote
New Grad, Entry LevelNanoCure AI is developing a next-generation, drug-free cancer treatment platform and is seeking a recent graduate Machine Learning Engineer. The role involves supporting and hardening training and inference pipelines, focusing on data correctness, model training infrastructure, and operational reliability.
Nanotechnology
Responsibilities
Support and extend PyTorch-based training pipelines for binary and multi-class cell classification
Implement and validate dataset loading, split isolation, class balancing, and evaluation metrics
Assist in managing stain variability, preprocessing pipelines, and controlled augmentations
Help diagnose failure modes such as class bias, threshold instability, and domain shift
Maintain FastAPI-based inference services running on NVIDIA Jetson Orin platforms
Assist with model loading, runtime configuration, thresholding logic, and decision gating
Help ensure inference outputs are deterministic, traceable, and compatible with downstream systems
Support multiple inference services running concurrently (e.g., parallel models, ports, or variants)
Build tooling and scripts to verify dataset integrity (duplicate detection, label correctness, leakage checks)
Assist with logging, monitoring, and basic performance profiling of training and inference runs
Help enforce reproducibility (seeds, configs, checkpoints, EMA handling)
Work closely with senior ML, systems, and embedded engineers to integrate models into a larger hardware-software system
Interface with lab personnel to understand real-world data issues (imaging variability, staining differences, capture artifacts)
Participate in technical reviews focused on correctness, not hype
Qualification
Required
Bachelor's or Master's degree in Computer Science, Electrical Engineering, Biomedical Engineering, or related field (recent graduate or early career)
Strong Python proficiency with hands-on experience using PyTorch
Solid understanding of supervised learning
Solid understanding of train/validation/test separation
Solid understanding of loss functions and class imbalance
Solid understanding of evaluation metrics (precision/recall, balanced accuracy, ROC behavior)
Familiarity with Linux development environments
Comfort working with existing codebases and improving them incrementally and safely
Ability to reason about why a model is behaving incorrectly, not just how to make it train
Preferred
Experience deploying models on embedded or edge devices (Jetson, CUDA, TensorRT)
Exposure to computer vision or biomedical imaging
Familiarity with FastAPI, REST services, or basic systemd/Linux services
Experience with experiment tracking, logging, or dataset tooling
Coursework or projects involving ML systems, not just notebooks
Benefits
Up to 10% equity
Company
NanoCure AI R&D Foundation for Cancers and Diseases
NanoCure AI R&D Foundation for Cancers and Diseases is a Texas-based nonprofit organization dedicated to developing next-generation, drugless therapeutic and diagnostic technologies for hematologic cancers and blood disorders.
Founded in 2025
2-10 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase