Senior Data Science Engineer_718 at Allianz Technology

Barcelona, Catalonia, Spain -

Full Time

Start Date

Immediate

Expiry Date

20 Dec, 25

Salary

0.0

Posted On

21 Sep, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, APIs, Containerization, Database Technologies, Software Engineering, Model Deployment, Prompt Engineering, LLM Development, Version Control, CI/CD, Digitalization, Automation, Frontend Technologies, Model Orchestration, Semantic Search, Knowledge Retrieval

Industry

Financial Services

Description

About the Job Allianz Technology is delivering and operating Allianz Partner’s E2E target solutions for all Lines of businesses globally such as Mobility & Assistance, Travel insurance, ticketing, banking partners, mobile devices and digital risk protection (MDDR). This covers the central “ACM B2B2C” target platform, which supports B2C, B2B, B2B2C channels. As a Senior ML/LLM Data Science Engineer, based in Barcelona, you will be taking part of a newly created cross-functional agile squad, focused on discovering, designing, implementing and delivering machine learning solutions, from model conception and development to building robust, scalable APIs and integrating them into enterprise production business applications, as well as contributing to world-wide rollouts, and guaranteeing Product harmonization, simplification, by embracing Digitalization & Automation at scale. What you do Design, build, and maintain scalable and secure RESTful APIs, and potentially GraphQL endpoints, for serving machine learning models and LLM-powered features using frameworks like FastAPI, Flask, or Django, including implementing API authentication, authorization, rate limiting, and comprehensive documentation. Collaborate with frontend and backend teams to integrate ML/LLM functionalities into applications, understanding data flow and interaction points, with optional familiarity in frontend technologies like React, Vue.js, or Angular. Implement resilient model deployment strategies using containerization technologies like Docker and Kubernetes, serving models efficiently on platforms like AzureML, Databricks, AWS SageMaker, Google Cloud AI Platform, or dedicated serving tools. Architect and manage model orchestration within application workflows using tools like Airflow, Prefect, Dagster, or Kubeflow Pipelines, ensuring efficient integration and management. Experience with various database technologies, including SQL (PostgreSQL, MySQL) and NoSQL (MongoDB) databases, as well as vector databases for supporting ML features. Apply software engineering best practices, including version control (Git), CI/CD pipelines for automated testing and deployment, writing clean, maintainable code, providing technical specifications, leadership, and maintaining software development environments. Ensure compliance and quality of specifications and guidelines, supporting architecture and production teams in organizing development processes, defining automated testing strategies, and supervising deployment of new applications and services. What you bring Architect and implement solutions using LLMs (e.g., GPT-4, Claude 3, Llama 3, Gemini) via APIs or by fine-tuning open-source models for tasks like extraction, classification, summarization, content generation, and conversational AI. Proficiency with LLM application development frameworks such as LangChain, LlamaIndex, and Haystack for building complex, orchestrated LLM workflows. Skilled in prompt engineering, fine-tuning techniques (e.g., LoRA, QLoRA), and designing Retrieval Augmented Generation (RAG) systems. Experience with vector databases (e.g., Pinecone, Weaviate, ChromaDB, FAISS) for semantic search and knowledge retrieval. Full proficiency in English with excellent communication and leadership skills. University degree or equivalent education in Computer Science, Software Engineering, or a similar qualification. Minimum 7-10 years of work experience in digital software development. What we offer We offer a hybrid work model which recognizes the value of striking a balance between in-person collaboration and remote working incl. up to 25 days per year working from abroad. We believe in rewarding performance and our compensation and benefits package includes a company bonus scheme, pension, employee shares program and multiple employee discounts (details vary by location). From career development and digital learning programs to international career mobility, we offer lifelong learning for our employees worldwide and an environment where innovation, delivery and empowerment are fostered. Flexible working, health and wellbeing offers (including healthcare and parental leave benefits) support to balance family and career and help our people return from career breaks with experience that nothing else can teach.

Responsibilities

Design, build, and maintain scalable and secure RESTful APIs for serving machine learning models. Collaborate with teams to integrate ML functionalities into applications and ensure efficient model deployment strategies.