ML Engineer – Wildlife Vision & Real-Time Predictions

Ebsco Subscription Services España SL; Massachusetts; On-site; USD 120,000 - 180,000; Full time

Job summary

Moultrie, headquartered in Birmingham, Alabama, is seeking a Machine Learning Engineer to own the prediction ML lifecycle from tagged camera images to deer movement predictions and hunt location optimization.

You will design, train, and deploy the prediction layer that turns behavioral data into actionable stand recommendations for hunters, defining the platform's technical direction in a high-impact, autonomous role.

Qualifications

• 4+ years of experience in machine learning engineering with demonstrated production deployments.
• Deep proficiency in PyTorch; experience with Ultralytics/YOLO or similar detection frameworks strongly preferred.
• Solid understanding of CNN architectures, transfer learning, and domain adaptation.
• Experience deploying models at scale on GPU infrastructure (AWS SageMaker, GCP Vertex AI, or equivalent).
• Proficiency in Python and familiarity with data pipeline tooling (Kafka, Airflow, or similar).
• Strong fundamentals in ML evaluation -confusion matrices, mAP, precision/recall tradeoffs and the ability to diagnose model failures.
• Familiarity with time-series prediction models (LSTMs, Prophet, XGBoost for temporal data).
• Experience with re-identification (RelD) or few-shot learning tasks.
• Prior work on wildlife imagery, agricultural computer vision, or similar low-contrast, occlusion-heavy domains.
• Experience with Microsoft Azure.
• Passion for the outdoors or hunting is a genuine plus -domain empathy makes better products.

Responsibilities

• Design and train object detection and classification models (YOLOv8, RT-DETR, or similar) to identify deer presence, sex, age class, and antler characteristics in trail camera imagery.
• Build and maintain the end-to-end ML pipeline: data ingestion from cloud storage, preprocessing, model training on GPU clusters, evaluation, and deployment via Triton, TorchServe, or similar.
• Develop individual deer re-identification models using coat patterns and antler morphology to track specific animals across cameras and time.
• Engineer features from vision outputs and environmental data (weather, terrain, moon phase, rut calendar) to feed downstream behavioral prediction models.
• Integrate ML Ops tooling - Mlflow or Weights & Biases - for experiment tracking, model versioning, and staged production deployments.
• Collaborate with Data Engineering to optimize data pipelines and with the Wildlife Biologist advisor to validate model outputs against real-world deer behavior.
• Monitor model performance in production and implement retraining pipelines to address data drift over seasons.

Skills

PyTorch expertise

CNN architectures

Time-series prediction

Model evaluation

Python programming

Tools

YOLO / Ultralytics

TorchServe / Triton / MLops tools

Mlflow / Weights & Biases

AWS SageMaker

GCP Vertex AI

Kafka / Airflow

Job description

Moultrie, headquartered in Birmingham, Alabama, is seeking a Machine Learning Engineer to own the prediction ML lifecycle from tagged camera images to deer movement predictions and hunt location optimization.

You will design, train, and deploy the prediction layer that turns behavioral data into actionable stand recommendations for hunters, defining the platform's technical direction in a high-impact, autonomous role.