About us Owkin is an AI company on a mission to solve the complexity of biology. It is building the first Biology Super Intelligence (BASI) by combining powerful biological large language models, multimodal patient data, and agentic software. At the heart of this system is Owkin K, an AI copilot and its new LLM fine-tuned on biology called Owkin Zero, used by researchers, clinicians, and drug developers to better understand biology, validate scientific hypotheses, and deliver better diagnostics and therapies faster. Please submit your CV in English About the role: We are seeking a detail-oriented and curious Bioinformatics Pipeline Developer to join our team. In this role, you will be at the intersection of biology and big data, helping to build and maintain the "highways" that process genomic, transcriptomic, clinical and other types of biological data. You won’t just be running scripts; you’ll be optimizing how we integrate diverse biological layers - from DNA sequencing to single-cell RNA-seq - to uncover clinical insights. In particular, you will: - Build, test, benchmark, maintain and update automated workflows (AirFlow or Snakemake) for processing sequencing (WES/WGS, bulk and single-cell RNAseq, spatial transcriptomics) and other clinical, imaging and molecular data types. - Implement strategies to ensure data quality, consistency and interoperability. - Calculate, implement, benchmark and integrate biological information and scores based on biomedical scientist’s input. - Maintain clear, version-controlled codebases (GitHub) and technical documentation. About you Required Skills & Qualifications - A relevant education in bioinformatics, computational biology, computer science, or a related field (Bachelor, Master or PhD), with proven experience gained in industry or academia. - Proficiency in Python. - Experience of developing bioinformatic pipelines. - Experience working in cloud environments. - Familiarity with orchestration tools and frameworks - Experience with NGS tools such as variant calling and RNAseq analysis. - Basic understanding of biological processes such as NGS library preparation (e.g., Illumina, RNA-seq) and the biological differences between tissue types (e.g., enterocytes vs. colonocytes). - Comfortable using Git for collaborative development. Nice-to-Haves - Proficiency in R. - Experience with Docker or Singularity containers. - Familiarity with single-cell/spatial transcriptomic analysis (Scanpy). - Knowledge of oncology-specific databases (TCGA, gnomAD, COSMIC). Reference: #LI-HB1 What we offer - Flexible work organization - Friendly and informal working environment - Opportunity to work with an international team with high technical and scientific backgrounds Recruitment Process & Security - Please complete the form and submit your CV. - Owkin is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, sex, gender, sexual orientation, age, color, religion, national origin, protected veteran status or on the basis of disability. - Owkin is a great place to work. As a coveted workplace we are, unfortunately, vulnerable to recruitment phishing scams. We urge all job seekers and candidates to be wary of potential scams. Most of these have individuals posing as representatives of prominent companies, including Owkin, with the aim of obtaining personal, sensitive, or financial information from applicants. These scams prey upon an individual’s desire to obtain a job and can sometimes “feel” like a genuine recruitment process. Some red flags are identified below. Should you encounter a recruitment process that claims to be for Owkin but is not consistent with the below, please do not provide any personal or financial information: - Legitimate Owkin recruitment processes include communication with candidates through recognized professional networks, such as LinkedIn. - Communication is always through an official Owkin email address (from the @owkin.com domain), over the phone or through our applicant tracking system (Greenhouse). - The Owkin talent team do use platforms such as LinkedIn and Job Teaser, however if you have any concern or doubt about this contact, please ask for them to send an email from @Owkin.com. - The Owkin talent team will not solicit personal data from candidates during the application phase including, but not limited to, date of birth, social security numbers, or bank account information; - Legitimate Owkin interviews may be conducted over the phone, in person, or via an approved enterprise videoconferencing service (Google Meets). They will not occur via Signal, Telegram or Messenger - Owkin offers of employment are based on merit and only extended once a candidate has interviewed with members of the talent and hiring team. Offers will be extended both verbally and in written format. If you think that you have been a victim of fraud, - Check the identity of the talent team on LinkedIn - Check our senior team on our website https://owkin.com/team/ - Check the existence of the position on our website: https://www.owkin.com/careers#current-opportunities - Notify Owkin's recruitment unit at this address hiring@owkin.com - contact the following authorities: - [FR] https://internet-signalement.gouv.fr/ - [UK] https://www.actionfraud.police.uk/reporting-fraud-and-cyber-crime - [US] https://reportfraud.ftc.gov/

Description and Requirements GG10.2 Data Engineer plays a critical role in data and analytics life cycle and significantly contributes to production grade data and analytics solutions. The role requires one to demonstrate Big Data, Engineering and Cloud expertise.It is an individual contributor role, expected to independently function 5-8+ years of relevant experience Bachelors degree in computer science, information technology or equivalent educational qualification • Design, build, and maintain robust ETL/ELT pipelines on cloud(Azure) or on-prem to collect, ingest and store large volumes of structured and unstructured data for batch/real time processing• Monitor, optimize, and troubleshoot data pipelines to ensure reliability, scalability, and performance• Ensure data processing, quality, security, and compliance guidelines, policies and standards are followed• Collaborate with multiple partners from Business, Technology, Operations and D&A capabilities (Data Governance, Data Quality, Data Modeling, Data Architecture, Data science, DevOps, BI & insights) • SQL, Python/Scala• NoSql and distributed databases (Hbase, Cosmos DB)• ETL pipleine development• Big Data Frameworks : Apache Spark, Hadoop, Hive• Cloud platforms: Azure data factory, Eventhub, Azure functions, Synapse, Databricks• Datawarehouses, data marts, data lakes• Medallion architecture• Performance tuning, optimization, and data quality validation• Real-time and batch data processing , streaming pieplines with Spark• Communication skills, analytical skills, structured problem-solving skills.,• Partner, Stakeholder engagement experience • DevOps practices: Git, AzureDevops, CI/CD pipelines• Unix shell scripting, MongoDB, Nifi• Exposure to Gen AI technology and tools About MetLife Recognized on Fortune magazine's list of the "World's Most Admired Companies" and Fortune World's 25 Best Workplaces™, MetLife, through its subsidiaries and affiliates, is one of the world's leading financial services companies; providing insurance, annuities, employee benefits and asset management to individual and institutional customers. With operations in more than 40 markets, we hold leading positions in the United States, Latin America, Asia, Europe, and the Middle East. Our purpose is simple - to help our colleagues, customers, communities, and the world at large create a more confident future. United by purpose and guided by our core values - Win Together, Do the Right Thing, Deliver Impact Over Activity, and Think Ahead - we're inspired to transform the next century in financial services. At MetLife, it's #AllTogetherPossible . Join us! #BI-Hybrid

Role Description - Analyse und Ausarbeitung konkreter Use Cases unserer Kunden zur Nutzung daten- und KI-basierter IT-Lösungen - Erstellung praktisch umsetzbarer Lösungskonzepte – technisch, fachlich und architektonisch - Entwicklung von PoC-, MVP- und produktreifen Anwendungen auf Cloud- und On-Premise-Stacks - Einsatz moderner LLM-Technologien: Embedding, Re-Ranking, Prompting, Fine-Tuning, Retrieval-Konzepte und weitere Methoden, sofern sie den Kundennutzen steigern - Enge Zusammenarbeit mit unseren Architekten, Beratern und Kunden zur Integration der Lösungen in bestehende Systemlandschaften - Mitarbeit bei der Weiterentwicklung unserer Produktlinien (QI-Box, QI-Flow) und unseres standardisierten Einführungsprozesses Qualifications - Mindestens 5 Jahre Berufserfahrung in AI/Data Science/Machine Learning/Data Engineering - Sehr gute Kenntnisse in Python sowie in gängigen ML-/DL-Frameworks (PyTorch, TensorFlow, Scikit-learn) - Fundierte Erfahrung mit LLMs, RAG-Systemen, Embeddings und Evaluationsverfahren - Sicherer Umgang mit relationalen Datenbanken, SQL sowie Vektor-Datenbanken - Erfahrung im Aufbau robuster Datenpipelines und grundlegende Kenntnisse in MLOps - Arbeit mit strukturierten Daten (z.B. Zeitreihen) und unstrukturierten Daten (Texte, PDFs, Dokumente) - Erfahrung mit Cloud- oder On-Premise-Umgebungen (AWS, Azure, GCP) - Verständnis für containerisierte Deployments, API-Design und Integrationen - Strukturierte und eigenständige Arbeitsweise - Präzise Kommunikation, Teamfähigkeit und Freude an interdisziplinärer Zusammenarbeit - Fähigkeit, komplexe technische Sachverhalte für Kunden verständlich aufzubereiten Benefits - Anspruchsvolle Projekte und viel eigene Verantwortung für Deine Arbeit - Offenheit für Veränderungen und die Bereitschaft, gemeinsam noch besser zu werden - Exzellentes technisches Equipment mit aktueller Hardware und freier Betriebssystemwahl - Flexibilität durch familienfreundliche Arbeitszeit im Rahmen der Vertrauensarbeitszeit - Mitarbeiter Benefits wie Jobrad, Fitness Abo, betriebliche Altersvorsorge, u.v.m.

Role Description Can you imagine a world where business and digital solutions will be truly seamless and where users will help companies to co-create them? Do you want to help us to shape this human-centred world? Welcome to UNGUESS. UNGUESS is the crowdsourcing platform for effective testing and real insights that enable tech, digital and business leaders to make smarter decisions, faster. How? Unleashing the power of the crowd, a community of highly engaged people all over the world that allows us to bring end-customer insights into the design, development, and testing phases of a product. This is not a traditional data engineering position. Around 60–70% of your work will focus on GenAI, RAG systems, vector search, and natural language understanding (NLU). The remaining part will cover classic data engineering responsibilities such as ETL pipelines and data modeling. You won’t just maintain existing systems, you’ll be the first building block of something new, laying the foundations for a knowledge base that transforms raw testing data into intelligent, queryable insights. As our first dedicated Data Engineer, you will be the architect of the infrastructure that makes this vision possible. You’ll own the design, implementation, and scalability of our data stack, working closely with the product and development teams. We are a rapidly growing tech company with the ambition of building an LLM-queryable Knowledge Base by leveraging existing but currently unstructured data sources. We do not yet have a dedicated data team: this role will be the first hire, with full ownership over architecture, implementation, and scalability. Responsibilities - Design and implement data ingestion and normalization pipelines from heterogeneous sources (APIs, files, databases, streams). - Build a data lake on AWS (S3, Glue, Athena) and orchestrate data flows using CDK. - Implement RAG (Retrieval-Augmented Generation) systems using vector databases and LLM models (Bedrock, OpenAI, LangChain). - Model metadata and define chunking strategies for NLU-queryable documents. - Ensure data security, governance, monitoring, and cost optimization. - Collaborate with the Product team to integrate the knowledge base into the existing platform. Requirements - GenAI & Vector Search: Hands-on experience with RAG systems in production, embedding models (OpenAI, Cohere, Amazon Titan), and vector databases (OpenSearch, Pinecone, pgvector). - Strong grasp of chunking strategies, retrieval optimization (precision/recall/reranking). - Proven expertise with AWS CDK, data services (S3, Glue, Athena, Lambda, Step Functions), and ML/AI workloads (Bedrock, SageMaker). Solid understanding of IAM, KMS, VPC for security/compliance. - Has a builder's mindset and enjoys designing robust, scalable solutions. Nice to have - Hands-on with serverless architectures and cost-optimized scaling strategies. - Experience in cloud-native environments and CI/CD (AWS). - Familiarity with monitoring and alerting (CloudWatch, X-Ray). Benefits - Compensation: €45,000 to €50,000/year gross salary and competitive MBO bonus - this range is a guideline; we’re first and foremost looking for the right person, the final offer will be shaped around you and reflect your skills and experience. - Remote work lovers. - Fast-track growth opportunities. - Access to group and personal training programs. Please note that this job advertisement is open to applicants of all genders, in accordance with Laws 903/77 and 125/91.