Senior Machine Learning (ML) Engineer

Micron Agritech; Dublin; On-site; EUR 70,000 - 100,000; Full time

Job summary

An innovative tech start-up in Dublin is seeking a Senior Machine Learning Engineer to lead efforts in developing and deploying computer vision models. The role encompasses the entire ML lifecycle, ensuring optimal performance in an agile setting. Applicants should have at least 5 years of ML experience, especially in computer vision, along with strong programming and technical skills. This position offers an exciting opportunity to contribute to groundbreaking technology in the animal health sector.

Benefits

Autonomy in project development

Innovative and fast-paced environment

Qualifications

• Minimum 5 years of hands-on experience in Machine Learning, with at least 3 years in computer vision.
• Strong Python engineering skills for data pipelines and automation.
• Proficiency with PyTorch or TensorFlow.

Responsibilities

• Develop and deploy computer vision models for automated detection and classification.
• Optimize deep learning models for various conditions.
• Collaborate with software engineers on ML tool integration.

Skills

Machine Learning

Deep Learning

Computer Vision

Python

SQL

Postgres

PyTorch

TensorFlow

Education

Bachelor’s degree in Computer Science, Engineering, or a related field

Master’s degree preferred

Tools

Docker

Git

CI/CD

Job description

Micron Agritech is a multi-award-winning Irish start-up bringing the AI revolution to animal health. Ingenuity and innovation are at the forefront of our company, and our diverse, fast-paced team is driving our vision of creating a more sustainable future for animals.

Digital transformation offers huge potential for the animal health sector, and Micron Agritech is leading the way with disruptive technologies that enable rapid diagnostics on-site, tools for disease modelling and prediction.

About the Role

We are looking for a Senior Machine Learning Engineer to develop and deploy computer vision models for automated detection, classification, and counting. You will own the full ML lifecycle - from data extraction and video-quality validation to model training, optimisation, and deployment into our production environment.

Key Responsibilities

1. Data, Video & Annotation Management

• Collaborate with the validation team to understand and review annotations.
• Extract datasets directly from Postgres using SQL and analyse data distributions.
• Clean, preprocess, and structure image and video datasets.
• Implement video-quality checks (blur, brightness, orientation, motion, duration).
• Perform dataset balancing, augmentation, and versioning.

2. Model Development

• Build and optimise deep learning models for object detection, classification, and counting.
• Conduct experiments with proper tracking (MLflow, W&B) and reproducibility.
• Evaluate models using mAP, precision, recall, and F1-score.
• Ensure robustness across diverse image/video conditions.
• Experience with architectures such as CNNs and transformer-based models (e.g., DETR, ViT).

3. Inference & Deployment

• Develop efficient inference pipelines for cloud, edge, or mobile environments.
• Optimise models using ONNX, TensorRT, quantisation, or similar tools.
• Package and deploy models using Docker, GitHub Actions, and AWS (EKS, Lambda, S3).
• Monitor production performance and iterate based on runtime metrics.

4. Collaboration & Documentation

• Work with software engineers to integrate ML outputs into applications.
• Coordinate with product and validation teams to refine accuracy requirements.
• Maintain documentation on datasets, model versions, training processes, and deployments.
• Contribute to CI/CD workflows for ML components.

Required Skills

• Minimum 5 years of hands‑on experience in Machine Learning, including at least 3 years focused on computer vision or deep learning.
• Bachelor’s degree in Computer Science, Engineering, or a related field; Master’s degree preferred.
• Strong Python engineering skills (data pipelines, automation, tooling).
• Proficiency with PyTorch or TensorFlow.
• Solid experience in computer vision and video processing (OpenCV, ffmpeg).
• Strong SQL skills and experience with Postgres or similar databases.
• Familiarity with Docker, Git, and CI/CD (GitHub Actions).
• Experience deploying ML models in production (AWS preferred).
• Strong analytical and problem‑solving abilities.

Nice to Have

• Experience with biological or diagnostic imaging datasets.
• Knowledge of classical CV algorithms.
• Familiarity with MLOps tools (MLflow, DVC, W&B).
• Experience working with frame‑level video analysis or optical flow.
• Familiarity with transformer-based computer vision models (DETR, ViT, Swin Transformer).

This is a great opportunity for someone that wants to own a project with high impact. You will be given autonomy and responsibility for an exciting development in a fast-paced and innovative team working at the cutting edge of technology, AI and veterinary medicine.