Wildlife Vision ML Engineer – Deer Detection & Prediction

PRADCO Inc.; Massachusetts; On-site; USD 120,000 - 150,000; Full time

Job summary

PRADCO Inc. is hiring a Machine Learning Engineer in Massachusetts for an onsite role. You will design and train object detection models, build end-to-end ML pipelines, and develop deer re-identification methods using coat patterns. Collaborate with data engineers and a wildlife biologist to validate outputs.

You will deploy on GPU infrastructure (AWS SageMaker, GCP Vertex AI), using Mlflow or Weights & Biases for experiment tracking and retraining to handle data drift across seasons.

Qualifications

• 4+ years of experience in machine learning engineering with production deployments.
• Strong PyTorch proficiency, with experience in Ultralytics/YOLO or similar detection frameworks.
• Deep understanding of CNN architectures, transfer learning, and domain adaptation.
• Experience deploying models at scale on GPU infrastructure (AWS SageMaker, GCP Vertex AI).
• Proficiency in Python and data pipeline tooling like Kafka and Airflow.
• Solid ML evaluation skills (confusion matrices, mAP, precision/recall) and diagnosing failures.
• Familiarity with time-series methods (LSTMs, Prophet, XGBoost) for temporal data.

Responsibilities

• Design and train object detection/classification models for wildlife imagery.
• Build end-to-end ML pipeline: data ingestion, preprocessing, training, eval, deployment.
• Develop deer re-identification models using coat patterns and antler morphology.
• Create feature engineering by combining vision outputs with environmental signals.
• Establish ML Ops practices with Mlflow or Weights & Biases for experiment tracking.
• Collaborate with Data Engineering and Wildlife Biologist advisor; monitor production performance.

Tools

PyTorch

Ultralytics/YOLO

SageMaker

Vertex AI

Kafka

Airflow

Mlflow

Weights & Biases

Triton

TorchServe

AWS SageMaker

GCP Vertex AI

Python

CUDA/GPU

Job description

PRADCO Inc. is hiring a Machine Learning Engineer in Massachusetts for an onsite role. You will design and train object detection models, build end-to-end ML pipelines, and develop deer re-identification methods using coat patterns. Collaborate with data engineers and a wildlife biologist to validate outputs.

You will deploy on GPU infrastructure (AWS SageMaker, GCP Vertex AI), using Mlflow or Weights & Biases for experiment tracking and retraining to handle data drift across seasons.