OverviewAntes de solicitar este puesto, por favor, lea la siguiente información sobre esta ocasión que encontrará a continuación.
In this role you will own the end-to-end ML lifecycle for our search and recommendation intelligence, driving accurate and personalized content delivery for financial professionals.
You will shape how users discover critical information, collaborating across product, software, and data science teams.
This position combines information retrieval, NLP, and finance to solve impactful, scalable problems.
You'll join a fast-moving, innovative environment with a clear impact on decision-making workflows.
A strong hook is RavenPack's focus on AI-powered financial insights at scale.
Compensaciones / BeneficiosGrowth opportunitiesCompetitive salaryContinuous learningInnovative cultureDiversity and international environmentResponsabilidadesLead end-to-end design, development,



and deployment of ranking and retrieval models for relevant search resultsAdvance semantic search through fine-tuning/distillation of language models and embedding techniquesArchitect and implement scalable recommender systems to personalize user experiencesCollaborate with product managers, software engineers, and data scientists to translate business needs into technical solutionsStay ahead of trends in ML, NLP, and information retrieval, prototyping new ideasRequisitos principalesMaster's or PhD in Computer Science, ML, Data Science, or related quantitative field3+ years of production ML experience focused on Information Retrieval, Search, or Recommender xhfqzwm SystemsProficiency in Python and SQL or similar query languagesExperience with PyTorch or TensorFlow, Scikit-learn, and Hugging FaceHands-on experience with vector databasesStrong analytical mindset and quantitative problem-solving skillsExcellent English communication, both written and spokenclear, precise communicationcollaborative and agile mindsetability to translate business needs into technical solutionsPythonSQLPyTorch

📌 Senior Ml Engineer (España)
🏢 MindMatch
📍 España