AI Engineer

Huawei Finland R&D; Helsinki; On-site; EUR 50,000 - 70,000; Full time

Job summary

A leading technology firm in Finland is looking for a versatile AI Engineer to be part of their Cloud Content Security Lab in Helsinki. The role involves building and optimizing data pipelines, developing AI automation frameworks, and conducting performance evaluations for models. Candidates should have a Master's or PhD in relevant fields, expertise in Python and SQL, and a strong understanding of data privacy. The position is full-time and based on site, providing an opportunity to contribute to advanced AI solutions.

Qualifications

• 2+ years experience in ML Engineering, MLOps, or Data Engineering.
• Proven track record of deploying models in large-scale production environments.
• Experience prototype complex systems from scratch and define best practices.

Responsibilities

• Design and maintain automated data pipelines and data lakes.
• Develop and optimize automated AI training frameworks.
• Conduct experiments, testing and benchmark evaluations.
• Automate AI infrastructure for scalability and efficiency.
• Develop AI/ML based tools and applications.

Skills

Python

SQL

Big data tools (Spark/Kafka)

CI/CD for ML

Kubernetes

Docker

Data privacy principles (GDPR)

Adversarial ML

Education

Master or PhD in computer science, mathematics, statistics, computational linguistics or equivalent experience

Tools

Kubernetes

Docker

Job description

Huawei Consumer Business Group is the leader in the all-scenario AI life. It covers smartphones, PC and tablets, wearables, mobile broadband devices, family devices and device cloud services. Huawei Consumer Business Group is dedicated to delivering the latest technologies to consumers. We believe in creating safe, privacy-friendly, and high-quality products with great user experiences for our consumers.

The Cloud Content Security Lab at Helsinki Research Center is dedicated to driving technological advancements to protect the online safety of Huawei mobile users in Harmony OS ecosystem. We build advance AI detection solutions to ensure content safety and AI safety such as harmful content detection, agentic AI safety, machine unlearning. We are looking for a versatile AI Engineer to bridge the gap between data infrastructure and model production. You will be responsible for the entire lifecycle of our AI assets—from building the "pipes" that move and anonymize raw data to automating the frameworks that train, test, and release our models. Your goal is to create a high-efficiency, self-sustaining AI ecosystem that allows our researchers and stakeholders to iterate faster and with higher quality.

This is a full‑time consultant position based in Ruoholahti, Helsinki, where you will be employed by Huawei supplier.

Your main responsibilities are:

• Data Infrastructure: Design, build, optimize, and maintain automated data pipelines and data lakes. You will oversee the data governance, collection, anonymization, and annotation of datasets to ensure they are research-ready while improving overall data visibility and quality.
• AI Lifecycle Automation: Develop and optimize automated AI training frameworks & Continuous Delivery for AI models releases.
• Model Performance & Evaluation: Conduct experiments, testing, and benchmark evaluations. You will collaborate closely with stakeholders to analyze results and implement strategies to improve model performance.
• Infrastructure Optimization: Automate AI infrastructure to ensure high efficiency, scalability, and cost-effectiveness.
• Tooling & Applications: Develop AI/ML based tools and applications such as detection systems, chatbot, demonstrators, and develop internal benchmarks to measure our solutions against industry standards.
• SOTA Research: Stay at the forefront of the field by researching emerging technologies and evaluating state-of-the-art (SOTA) machine learning methods for practical integration.

Required Skills & Qualifications:

• Master or PhD in computer science, mathematics, statistics, computational linguistics or equivalent experience.
• Strong in Python, SQL, and big data tools (Spark/Kafka), CI/CD for ML and cloud orchestration (Kubernetes/Docker).
• 2+ years in ML Engineering, MLOps, or Data Engineering. Proven track record of deploying models and big data operations in large-scale production environments is a big plus.
• Solid understanding of data privacy principles (GDPR) and strong security mindset. Experience handling sensitive data especially anonymization, understanding of adversarial ML, or working within Trust & Safety tech stacks.
• Ability to architect complex systems from scratch and define best practices for data quality and model reliability.
• Full stack developer experience with hands‑on server‑side development, RESTful services, and web applications is a bonus.
• Experience with various public cloud environments and technologies.
• Candidates with ICPC, IOI/IMO, IOAI and other international competition in computer science, machine learning, and AI, etc. are highly preferred.

About Huawei

Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. With integrated solutions across four key domains – telecom networks, IT, smart devices, and cloud services – we are committed to bringing digital to every person, home and organization for a fully connected, intelligent world.

At Huawei, innovation focuses on customer needs. We invest heavily in basic research, concentrating on technological breakthroughs that drive the world forward.

We seek and reward talent! At Huawei, if you are dedicated to creativity, engagement of technical risks and delivery of target-driven results, your efforts will be rewarded with outstanding career prospects.

About Huawei Finland R&D

Huawei Finland Research Center was established in 2012. At our sites in Helsinki and Tampere, you will have an opportunity to be part of the leading research and development of future smart devices. We offer a career in a forward-looking industrial research team with a solid track record in innovation and publication and delivering its result as factual contributions to on-the-market devices.