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Senior Machine Learning Engineer

Berry AITaipei - NeihuEngineering
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Salary
Not listed
Job type
Full-time
Work mode
Remote
Posted
31 Jul 2026
Status
Open · checked 7d ago

About this role

Role Overview

Berry AI is hiring a Senior Machine Learning Engineer to join the engineering team in Taipei with remote flexibility. This role centers on owning end-to-end model development and transforming business requirements into reliable production systems for AI-powered restaurant platforms.

Key Responsibilities

Drive iterative advancements across the artificial intelligence and machine learning stack, focusing on object detection and tracking, vehicle and person re-identification, and edge video understanding.
Create efficient algorithms suitable for resource-constrained hardware by implementing optimization methods and lightweight architectures within strict compute and latency budgets.
Translate business goals into distinct algorithmic challenges by establishing metrics, executing experiments, and conducting thorough error analysis and ablation studies.
Collaborate closely with product engineers to deploy, monitor, and maintain machine learning systems in production environments, ensuring robust feedback loops and drift detection.
Enhance data and labeling quality through refined sampling strategies, clear annotation guidelines, and dataset maintenance tooling.

Requirements

Bring a minimum of five years of professional experience building production machine learning systems, supported by deep hands-on expertise in computer vision, multi-object tracking, and object detection.
Demonstrate strong machine learning and deep learning fundamentals encompassing statistics, classical methods, and deep neural network training dynamics and failure modes.
Possess advanced proficiency in Python alongside deep learning frameworks such as PyTorch or TensorFlow, including custom training loops, distributed training, and model debugging.
Show a proven history of driving independent research initiatives from metric selection and experimental design to honest interpretation of results.
Exhibit practical production sensibility including familiarity with inference engines like ONNX, TensorRT, or OpenVINO, performance profiling, and hardware deployment.

Nice to Have

Practical experience with MLOps practices including experiment tracking, model and data versioning, and reproducible workflows utilizing tools such as DVC or MLflow.
Familiarity with machine learning pipeline and workflow orchestration tooling like Dagster for training, evaluation, and deployment.
Background in large language models, retrieval-augmented generation, or agentic artificial intelligence, including fine-tuning techniques like LoRA or PEFT, vector stores, rerankers, LangChain, and vision-language models.

Skills and Tools

Python
PyTorch
TensorFlow
Computer Vision
MLOps
LLM
LangChain
RAG

About the Company

Berry AI builds innovative operations platforms tailored for quick-service restaurant brands, offering store management tooling, drive-thru analytics, and loss prevention systems deployed across thousands of United States locations. Computer vision remains at the absolute core of the technology shipped. The engineering culture emphasizes a small team size, high personal ownership, fast customer feedback, and the use of modern development tooling like coding agents and large language models.

How to Apply

To apply for this position, please visit the official Berry AI careers page to submit your application details.

Skills and tech stack

PythonPyTorchTensorFlowLLMComputer VisionLangChainRAGMLOps

Questions candidates ask

What is the primary focus of the Senior Machine Learning Engineer role?

The role focuses on owning model development end-to-end, building computer vision algorithms for edge hardware, and turning business needs into production systems.

Where is the position located?

The job is based in Taipei - Neihu with remote options available.

How many years of experience are required?

Candidates must have 5+ years of experience building production machine learning systems.

What technical frameworks and languages are required?

Python is required along with deep learning framework experience in either PyTorch or TensorFlow.

What bonus skills are beneficial for applicants?

Bonus skills include MLOps experience, workflow orchestration tools like Dagster, and experience with LLMs, RAG, or agentic AI frameworks.

Ready to apply?

The application is on the official Berry AI careers page.

Apply on company site