Job
Description
In this role, you will have the opportunity to design and develop solutions, contribute to roadmaps of Big Data architectures and provide mentorship and feedback to more junior team members
We are looking for someone to help us manage the petabytes of data we have and turn them into value Does that sound a bit like youLets talk! Even if you dont tick all the boxes below, wed love to hear from you; our new department is rapidly growing and were looking for many people with the can-do mindset to join us on our digitalization journey Thank you for considering DHL as the next step in your career we do believe we can make a difference together!What will you needUniversity Degree in Computer Science, Information Systems, Business Administration, or related field 2+ years of experience in the Data Scienctist / Machine Learning Engineer roleStrong analytic skills related to working with structured, semi structured and unstructured datasets Advanced Machine learningtechniques: Decision Trees, Random Forest, Boosting Algorithm, Neural Networks, Deep Learning, Support Vector Machines, Clustering, Bayesian Networks, Reinforcement Learning, Feature Reduction / engineering, Anomaly deduction, Natural Language Processing (incl sentiment analysis, Topic Modeling), Natural Language Generation Statistics / Mathematics: Data Quality Analysis, Data identification, Hypothesis testing, Univariate / Multivariate Analysis, Cluster Analysis, Classification/PCA, Factor Analysis, Linear Modeling, Time Series, distribution / probability theory and/or Strong experience in specialized analytics tools and technologies (including, but not limited to)Lead the integration of large language models into AI applications Very good in Python Programming Power BI, TableauDevelop the application and deploy the model in production Kubeflow, ML Flow, Airflow, Jenkins, CI/CD Pipeline As an AI/ML Engineer, you will be responsible for developing applications and systems that leverage AI tools, Cloud AI services, and Generative AI models Your role includes designing cloud-based or on-premises application pipelines that meet production-ready standards, utilizing deep learning, neural networks, chatbots, and image processing technologies Professional Technical Skills:Essential Skills:Expertise in Large Language Models Strong knowledge of statistical analysis and machine learning algorithms Experience with data visualization tools such as Tableau or Power BI Practical experience with various machine learning algorithms, including linear regression, logistic regression, decision trees, and clustering techniques Proficient in data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity Awareness of Apache Spark, HadoopAwareness of Agile / Scrum ways of working Identify the right modeling approach(es) for given scenario and articulate why the approach fits Assess data availability and modeling feasibility Review interpretation of models results Experience in Logistic industry domain would be added advantage Roles Responsibilities:Act as a Subject Matter Expert (SME) Collaborate with and manage team performance Make decisions that impact the team Work with various teams and contribute to significant decision-making processes Provide solutions to challenges that affect multiple teams Lead the integration oflarge language modelsinto AI applications Research and implement advanced AI techniques to improve system performance Assist in the development and deployment of AI solutions across different domains You should have:Certifications in some of the core technologies Ability to collaborate across different teams / geographies / stakeholders / levels of seniority Customer focus with an eye on continuous improvement Energetic, enthusiastic and results-oriented personality Ability to coach other team members, you must be a team player!Strong will to overcome the complexities involved in developing and supporting data pipelines Language requirements:English Fluent spoken and written (C1 level)An array of benefits for you:Hybrid work arrangements to balance in-office collaboration and home flexibility Annual Leave: 42 days off apart from Public / National Holidays Medical Insurance: Self + Spouse + 2 children An option to opt for Voluntary Parental Insurance (Parents / Parent -in-laws) at a nominal premium covering pre existing disease In House training programs: professional and technical training certifications
