AI Engineer

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 purposeThe 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 AccountabilitiesCollaboration & storytellingPartner with the AI Business Analyst to translate business needs into technical solutions and communicate insights back to colleagues from the business sideCommunicate data-driven opportunities to non-technical teams and stakeholdersGuide the AI Business Analyst in machine learning and data best practicesData quality & pipelinesCollect, clean, and prepare datasets from both internal and external sourcesAs ideas mature, design and implement automated ingestion pipelines (ETL/ELT)Apply basic validation frameworks and later monitor data drift/quality as models scaleModel development & experimentationBuild and test AI-models on structured and unstructured dataContainerize models using Docker and orchestrate with Kubernetes (when applicable)Compare proprietary AI APIs with OSS modelsSupport feature engineering, embeddings, and evaluation for AI use cases Integration & scalingProven skill & experience of deploying AI models into production in mid-size to large companiesCollaborate with the AI Software Architect to embed models into applicationsInitially implement lightweight MLOps practices, progressively advancing to CI/CD, MLflow, and containerization as organizational adoption increasesContribute to scalable AI services that can support multiple business functions in later phases Governance & complianceDocument 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 & SkillsBS/MS in engineering, analytics, or a related field3+ years in technical deployment, implementation of applied data science / ML experience (prototyping + scaling). Contributions to open-source AI projects is a plusExperience 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 competenciesPassionate about turning traditional workflows into AI-powered innovationsMotivated by a global, diverse environment. Enjoys collaborating across functions and culturesGood at bridging business needs with technical executionCommunicates clearly with non-technical audiences and builds trustDemonstrates curiosity and entrepreneurial skills in situations with open-ended possibilities.Structured problem-solving skills. Handles ambiguity and learns from rapid experimentationValues responsible AI, compliance, and explainabilityWhy join usShape the future: Help build our AI program from day one, defining its technical backbone and guiding how a global consumer goods industry leader embraces AIHands-on: Engage directly with complex business data, such as manual uploads and unstructured sources prior to implementing automation or data pipelinesCutting-edge stack: Leverage state-of-the-art AI solutions and frameworks to prototype, deploy, and scale solutionsHigh visibility: Your work makes AI credible, helps MVPs scale, and supports enterprise adoptionPlease 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 Brynil.Bjorke@mowi.com.