Digital Solutions, a division within Mowi Sales & Marketing, enhances business activities by leveraging technology. The team’s efforts centre on digitalising workflows, integrating cutting-edge technologies, and encouraging a data-driven mindset.

In this role, you’ll be at the centre of three global mega topics - healthy nutrition, sustainability, and artificial intelligence - shaping smarter food systems and driving Mowi’s Blue Revolution forward.

Role purpose

The AI Engineer is a core builder in the AI program, designing, developing, and validating machine learning models and data pipelines and support turning prototypes into scalable business solutions. Working alongside the AI Business Analyst, this role ensures experiments are backed by reliable data, robust models, and reproducible workflows - laying the foundation for enterprise adoption and governance.

Role Accountabilities

Collaboration & storytelling

• Partner with the AI Business Analyst to translate business needs into technical solutions and communicate insights back to colleagues from the business side
• Communicate data-driven opportunities to non-technical teams and stakeholders
• Guide the AI Business Analyst in machine learning and data best practices

Data quality & pipelines

• Collect, clean, and prepare datasets from both internal and external sources
• As ideas mature, design and implement automated ingestion pipelines (ETL/ELT)
• Apply basic validation frameworks and later monitor data drift/quality as models scale

Model development & experimentation

• Build and test AI-models on structured and unstructured data
• Containerize models using Docker and orchestrate with Kubernetes (when applicable)
• Compare proprietary AI APIs with OSS models
• Support feature engineering, embeddings, and evaluation for AI use cases

Integration & scaling

• Proven skill & experience of deploying AI models into production in mid-size to large companies
• Collaborate with the AI Software Architect to embed models into applications
• Initially implement lightweight MLOps practices, progressively advancing to CI/CD, MLflow, and containerization as organizational adoption increases
• Contribute to scalable AI services that can support multiple business functions in later phases

Governance & compliance

• Document assumptions, risks, and model performance to ensure AI models in production are auditable and compliant.
• Support AI governance (bias, fairness, explainability, GDPR/PIPL/PDPA)

Key Qualifications & Skills

• BS/MS in engineering, analytics, or a related field
• 3+ years in technical deployment, implementation of applied data science / ML experience (prototyping + scaling). Contributions to open-source AI projects is a plus
• Experience with building and maintaining scalable MLOps pipelines, MLOps tools (MLflow, experiment tracking, CI/CD, Docker/Kubernetes)
• Familiarity with vector databases (Weaviate, Milvus, Chroma) and orchestration frameworks (LangChain, LangGraph LlamaIndex)
• Proficiency in Python, including data libraries (Pandas, NumPy, scikit-learn)
• Strong SQL skills. Exposure to cloud data platforms (Snowflake, AWS, Azure, or GCP desirable)
• Experience with technical solution design and skilled in troubleshooting implementation issues.
• Knowledge of privacy and compliance frameworks (GDPR, PIPL, PDPA)

Key competencies

• Passionate about turning traditional workflows into AI-powered innovations
• Motivated by a global, diverse environment. Enjoys collaborating across functions and cultures
• Good at bridging business needs with technical execution
• Communicates clearly with non-technical audiences and builds trust
• Demonstrates curiosity and entrepreneurial skills in situations with open-ended possibilities.
• Structured problem-solving skills. Handles ambiguity and learns from rapid experimentation
• Values responsible AI, compliance, and explainability

Why join us

• Shape the future: Help build our AI program from day one, defining its technical backbone and guiding how a global consumer goods industry leader embraces AI
• Hands-on: Engage directly with complex business data, such as manual uploads and unstructured sources prior to implementing automation or data pipelines
• Cutting-edge stack: Leverage state-of-the-art AI solutions and frameworks to prototype, deploy, and scale solutions
• High visibility: Your work makes AI credible, helps MVPs scale, and supports enterprise adoption

Please note, we retain the right to close this vacancy or keep it open subject to volume and quality of applications. We would, therefore, encourage candidates to submit an application as soon as possible.

For questions, contact AI and Innovation Lead Brynil Bjørke at [email protected].