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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and developing AI solutions using Machine Learning, Generative AI, and Large Language Models, with a strong focus on deploying scalable and maintainable systems. Proficient in statistical analysis, data preparation, and ensuring responsible AI development aligned with security and regulatory standards.
Highest-signal resume keywords
Machine LearningGenerative AILarge Language ModelsPython ProgrammingCloud Platforms
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningStatistical AnalysisData ScienceAI Solution DevelopmentData PreparationEvaluation ApproachesAI TestingAPIs IntegrationMLOpsCloud-Native Technologies
Soft Skills
Analytical SkillsProblem-Solving SkillsCommunication SkillsCuriosityResult-Driven Mindset
Tools & Technologies
Microsoft AzureGitCI/CDDockerKubernetes
Certifications & Qualifications
Master’s Degree in Computer ScienceMaster’s Degree in Information SciencesMaster’s Degree in Artificial IntelligenceMaster’s Degree in Machine LearningMaster’s Degree in Data Science
Industry Keywords
AI DevelopmentEnterprise ApplicationsKnowledge ManagementAgile MethodologiesHR Domain
Tech Stack
Tools & technologiesAzureCloudDockerKubernetesPython
About the role
Key responsibilities & impact- Design and develop AI solutions using machine learning, Generative AI, Large Language Models, retrieval-based systems and agentic AI
- Apply statistical techniques, machine learning and data analysis to solve complex business problems and identify automation and optimization opportunities
- Develop solutions using Large Language Models and foundation models for natural language, documents, enterprise knowledge and business processes
- Translate business problems into effective AI solutions and select appropriate models, techniques, data sources and technologies
- Prepare and structure data and knowledge for AI systems, ensuring quality, relevance and appropriate use
- Define evaluation approaches and assess the quality, reliability and effectiveness of AI solutions before and after deployment
- Deploy AI solutions to production with scalability, maintainability, security and operational reliability
- Monitor AI solutions and continuously improve performance using operational data, user feedback and evaluation results
- Stay current with machine learning, Generative AI and agentic AI developments and assess emerging technologies
- Collaborate with business experts, engineers, architects, product teams and other stakeholders
- Ensure responsible AI development considering security, privacy, transparency, governance and regulatory requirements
- Contribute reusable AI practices, patterns and capabilities and share knowledge across the organization
Requirements
What you’ll need- Master’s degree in Computer Science, Information Sciences, Artificial Intelligence, Machine Learning, Data Science or a related field
- At least 5–7 years of experience in Data Science, Machine Learning, Artificial Intelligence or a related role
- Strong knowledge of machine learning, statistical analysis and modern AI techniques
- Strong programming skills, particularly in Python, and experience with relevant data science and AI libraries
- Experience developing AI solutions using structured and unstructured data
- Hands-on experience with Generative AI and Large Language Models, or comparable modern AI technologies
- Understanding of techniques for connecting AI systems with enterprise data and knowledge
- Experience designing evaluation and testing approaches for AI solutions
- Ability to contribute to production-ready AI solutions
- Experience with cloud platforms, preferably Microsoft Azure, and modern software development practices including Git and CI/CD
- Good understanding of APIs and integration of AI capabilities into applications and business processes
- Excellent analytical and problem-solving skills
- Strong communication skills, with the ability to explain complex AI concepts and results to technical and non-technical audiences
- Curiosity, eagerness to learn and comfort working with rapidly evolving technologies and best practices
- Pragmatic and result-driven mindset focused on business value and usability
- Experience with Generative AI, Large Language Models, retrieval-based AI or agentic AI systems is a plus
- Experience developing AI solutions interacting with enterprise applications, data sources or APIs is a plus
- Experience with cloud-native technologies such as Docker and Kubernetes is a plus
- Experience with MLOps/LLMOps, monitoring and operationalisation of AI solutions is a plus
- Experience with AI evaluation, experimentation and automated testing approaches is a plus
- Experience developing AI products used in real business processes is a plus
- Experience working in Agile, multidisciplinary teams is a plus
- Experience in HR, payroll or another complex and knowledge-intensive business domain is a plus
Benefits
Comp & perks- Comprehensive training and development programs
- Flexible working schedule
- Private medical insurance 100% covered by SD Worx
- 25 vacation days
- 18 hours for personal matters
- Reduced summer hours: 36 hours instead of 40 per week, for 4 weeks (to be chosen in July or August)
- Cobee flexible retribution options: meals, transportation, etc.
- Laptop and equipment provided
- Workation: possibility to work from abroad (where SD Worx has legal entity, up to 4 weeks per year)
- Learning opportunities: language courses (as per availability), individual training bonus, an individual development plan, and professional training
- Career growth opportunities