• Design, build, and validate machine learning models for RF emitter identification — including feature engineering from sensor data, training pipeline development, model evaluation, and iterative refinement based on results • Conduct hands-on exploratory data analysis on RF sensor datasets using Python and Jupyter notebooks — writing and running analytical code, characterizing feature distributions, identifying data quality issues, and producing documented findings • Implement and maintain ML data pipelines — ingesting NDF sensor streams, applying rollup and preprocessing logic, constructing training datasets, and ensuring pipeline correctness on constrained edge hardware with no cloud dependency • Collaborate with the technical lead and Principal AI/ML Engineer to investigate RF sensor data quality, attribution reliability, and feature behavior under contention — writing code to characterize error sources, validate assumptions, and reproduce findings • Produce clear technical documentation of experiments, model configurations, and results — maintaining reproducibility through disciplined versioning, and contributing to monthly status reports and team knowledge sharing

Wir sind CARIAD, das Automotive-Software-Unternehmen der Volkswagen Group. Unsere Teams entwickeln Softwareplattformen und digitale Kundenfunktionen für legendäre Marken wie Audi, Volkswagen und Porsche – und unterstützen so die Volkswagen Group auf ihrem Weg zum führenden automobilen Technologiekonzern. CARIDIANS in Softwarezentren in Deutschland, den USA, China, Estland und Indien arbeiten daran, die Automobilität für alle neu zu gestalten. DEIN TEAM Als Praktikant unterstützen Sie Teams, indem Sie theoretisches Wissen praktisch anwenden, wertvolle Praxiserfahrung sammeln und zu wichtigen Geschäftsaktivitäten beitragen. Der Schwerpunkt liegt auf Ihrer beruflichen Entwicklung durch betreute Aufgaben, die Wachstum und Zusammenarbeit fördern. Sie wirken aktiv an täglichen Abläufen und Projekten mit, erweitern Ihr Branchenwissen, Ihre technischen Fähigkeiten und arbeiten eng mit erfahrenen Fachleuten zusammen. DEINE AUFGABEN - Recherche zum aktuellen Stand der Technik sowie zu relevanten Algorithmen und Datensätzen - Implementierung und Benchmarking von Deep-Learning- oder geometrischen SLAM-Methoden für Baseline-Vergleiche - Entwicklung und Evaluation von Fusionspipelines für Radar- und Kameradaten - Testen und Validieren der Ergebnisse mit realen automobilen Daten Anforderungen an die Qualifikation - Sehr gute Studienleistungen - Eingeschriebener Studentin der Informatik, Robotik, Elektrotechnik, Mathematik oder eines vergleichbaren Studiengangs - Kenntnisse relevanter Sensoren für autonomes Fahren sowie Messtechnik - Programmierkenntnisse und Erfahrung in Python oder C++ - Sehr gute Englischkenntnisse in Wort und Schrift - Hohes Maß an Engagement, Eigeninitiative und Teamfähigkeit NICE TO KNOW - Möglichkeit für Remote-Arbeit innerhalb Deutschlands - Dauer: 3 – 6 Monate - 35 Stunden/Woche - Vergütung: 13,90 €/Stunde Bei CARIAD schätzen wir Individualität und Vielfalt – denn wir sind überzeugt, dass uns unsere Unterschiede stärker machen. Wir setzen uns aktiv dafür ein, Teams mit unterschiedlichen Hintergründen, Perspektiven und Erfahrungen aufzubauen. Unser Ziel ist ein Arbeitsumfeld, in dem sich alle wertgeschätzt fühlen und ihre Stärken einbringen können. Wenn du aufgrund einer Behinderung Unterstützung bei deiner Bewerbung brauchst, melde dich gerne bei uns unter careers@cariad.technology – wir helfen dir gerne weiter.

• As an MLOps Engineer, you will design, implement, and support the platforms, pipelines, and operational processes that enable scalable, secure, and reliable deployment of machine learning solutions for federal clients. • You will partner closely with data scientists, AI engineers, data engineers, and government stakeholders to operationalize models across development, testing, and production environments. • You will play a critical role in enabling secure AI and ML delivery within DoD and federal financial environments, ensuring models are repeatable, auditable, and compliant with federal standards. • Design, build, and maintain end‑to‑end MLOps pipelines, supporting model training, testing, deployment, monitoring, and retraining • Implement CI/CD workflows for ML models and data pipelines in secure federal environments • Operationalize machine learning models built by data science teams and ensure production readiness • Develop and manage model versioning, artifact management, and experiment tracking • Implement monitoring solutions for model performance, drift, data quality, and pipeline health • Automate infrastructure provisioning and deployment using infrastructure‑as‑code and DevOps best practices • Support auditability, explainability, and governance of AI/ML systems • Collaborate with stakeholders to align MLOps architectures with mission needs and security requirements

Company Description SmartRecruiters is the Recruiting AI Company that transforms hiring for the world’s leading enterprises. Built for global scale, SmartRecruiters, an SAP company, delivers an AI-powered hiring platform that automates and optimizes the entire talent acquisition process, ensuring faster and smarter hiring decisions. More than 4,000 companies, including Amazon, Visa, and McDonald's, rely on SmartRecruiters to build winning teams. In 2025, SmartRecruiters joined SAP, the global leader in enterprise applications. Together, SmartRecruiters and SAP are accelerating the reinvention of hiring by combining cutting-edge AI innovation with the scale, reach, and resources of SAP’s ecosystem. At SmartRecruiters, we are a values-driven, globally focused tech company with strong financial backing and a bold vision for the future of work. We commit and dig deep, embracing challenges with grit, curiosity, and a drive for excellence. We foster a collaborative and inclusive work environment, where trust and determination bring us together. Because together, we will win. Recognized by Fosway Industry Analysts as a strategic leader in recruitment technology for three consecutive years, and awarded by Comparably as a top company for Women, Perks and Benefits, Work-Life Balance, Happiness, Compensation, Diversity, and Culture - we take pride in creating a place where everyone can thrive. Our remote-friendly culture, competitive salaries, and strong internal mobility ensure that high performers have meaningful growth opportunities in an environment built on respect and empowerment. Job Description We are looking for a Senior Machine Learning Engineer to join our Chat Group, where we’re building the next generation of intelligent conversational systems for the recruiting industry. Our mission is bold yet simple: boost the efficiency of recruiting and hiring teams and deliver the most personalized experience ever - powered by cutting-edge ML, NLP, and agentic AI. You’ll play a central role in designing and developing agentic workflows, where autonomous AI agents collaborate, reason, and act to deliver intelligent and context-aware recruiting experiences at scale. At SmartRecruiters, you’ll be part of a global, high-impact team shaping how people connect with jobs. You’ll work with passionate peers across Germany, Poland, the UK, and the US - in a culture that values autonomy, innovation, and measurable outcomes. We’re not just building chat systems - we’re building the AI recruiting assistants of the future. Important: the position is available only under a standard contract of employment with 80% of tax deductible cost. What You’ll Do - Architect and build agentic workflows that combine large language models, reasoning components, and data pipelines to create adaptive, goal-driven conversational systems - Lead the design and development of advanced ML/NLP products, from ideation to production - including model training, evaluation, optimization, and deployment - Drive experimentation with new approaches for agentic reasoning, coordination, and autonomous system design - Collaborate closely with product and engineering teams to integrate intelligent agents into real-world recruiting workflows - Guide technical decisions, mentor other engineers, and help define best practices for scalable, maintainable ML systems - Contribute to the evolution of our NLP and conversational intelligence stack, focusing on reliability, personalization, and user impact - Proactively identify opportunities to automate, improve, and innovate within our chat-based ecosystem Qualifications - BSc or MSc in Computer Science, Machine Learning, AI, NLP, or a related technical field - or equivalent practical experience - 5+ years of experience developing and deploying machine learning systems in production - Proven expertise in NLP techniques, LLM fine-tuning, and model evaluation - Strong proficiency with deep learning frameworks (e.g., PyTorch, TensorFlow) and ML tools (e.g., scikit-learn, Hugging Face) - Advanced Python programming skills and solid software engineering fundamentals - Experience designing and maintaining end-to-end ML pipelines, from data ingestion to deployment - Hands-on experience with agentic workflows or building autonomous AI systems is a major plus - Familiarity with chatbots, conversational AI, or multi-agent systems is strongly preferred - Experience with data quality management, evaluation metrics, or observability in ML systems is a plus - Strong analytical thinking, creativity, and an ownership mindset - Excellent communication and collaboration skills in a cross-functional, international environment - Fluency in English, both written and spoken Additional Information SmartRecruiters is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.