Senior Data Scientist / Ml Engineer

Senior Data Scientist / ML EngineerLocation: Remote from Spain (an indefinite Spanish employment contract)Working hours:readiness towork till 2-3 PM EST hours (8-9 PM CET)Are you a skilled Machine Learning engineer with a passion for Computer vision, NLP or Generative AI?Do you have a knack for understanding both the technical intricacies and the business implications of data-driven solutions?If so, we have an exciting opportunity for you to join our team as Machine Learning Engineer.Requirements:*Education:Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related quantitative field.Experience:5+ years of professional experience in machine learning engineering, AI development, or a closely related role.Machine Learning & Statistics:Solid understanding of classical ML algorithms (e.g., tree-based models, SVMs, clustering, ensemble methods), feature engineering, model evaluation metrics, and statistical methods (hypothesis testing, regression analysis, probability distributions).LLM Expertise:Demonstrated project experience with large language models, including:Prompt engineering and prompt management strategies;LLM application development (end-to-end);Fine-tuning of large language models;Retrieval-augmented generation (RAG) pipeline design and implementation;Practical experience with vector stores such asChromaDB,pgvector, andPostgreSQL.AI Agents:Hands-on experience building AI agents and multi-agent systems using frameworks such asLangChain,LangGraph,CrewAI, or similar orchestration frameworks.Must demonstrate the ability to design agent architectures, manage tool integration, and handle complex agent workflows.Programming:Proficiency inPythonwith a strong emphasis on writing clean, maintainable, production-quality code.Familiarity with software engineering best practices (testing, code review, documentation).Cloud:Practical experience withGoogle Cloud Platform (GCP)services for ML workloads (e.g., Vertex AI, Cloud Run, GCS, BigQuery, Compute Engine).DevOps & MLOps:Docker:Proficiency in containerization - building, managing, and deploying Docker images and containers.GitLab:Proficient GitLab skills for version control, merge request workflows, and repository management.API Development:Experience withFastAPI, including request validation, async handling, and integration with ML model serving.Broader software development experience expected.At least B2 level of English.Soft Skills:Excellent communication skillsStrong work ethic and high personal accountabilityOwnership mentality - takes full responsibility for deliverables and outcomesProactive, self-starting approach to identifying problems and driving project success without waiting for direction.Responsibilities:Drive/Participate the ideation, development, and execution of POCs and AI related projectDevelop and implement machine learning models, algorithms, and data-driven solutions to address complex business problemsCollaborate cross-functionally with engineering, product management, and other relevant teams to integrate data-driven functionalities into our products

Are you a skilled Machine Learning engineer with a passion for Computer vision, NLP or Generative AI? Do you have a knack for understanding both the technical intricacies and the business implications of data-driven solutions? If so, we have an exciting opportunity for you to join our team as Machine Learning Engineer. Requirements: *Education:Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related quantitative field. Experience:5+ years of professional experience in machine learning engineering, AI development, or a closely related role. Machine Learning & Statistics:Solid understanding of classical ML algorithms (e.g., tree-based models, SVMs, clustering, ensemble methods), feature engineering, model evaluation metrics, and statistical methods (hypothesis testing, regression analysis, probability distributions). LLM Expertise:Demonstrated project experience with large language models, including: Prompt engineering and prompt management strategies; LLM application development (end-to-end); Fine-tuning of large language models; Retrieval-augmented generation (RAG) pipeline design and implementation; Practical experience with vector stores such asChromaDB,pgvector, andPostgreSQL. AI Agents:Hands-on experience building AI agents and multi-agent systems using frameworks such asLangChain,LangGraph,CrewAI, or similar orchestration frameworks. Must demonstrate the ability to design agent architectures, manage tool integration, and handle complex agent workflows. Programming:Proficiency inPythonwith a strong emphasis on writing clean, maintainable, production-quality code. Familiarity with software engineering best practices (testing, code review, documentation). Cloud:Practical experience withGoogle Cloud Platform (GCP)services for ML workloads (e.g., Vertex AI, Cloud Run, GCS, BigQuery, Compute Engine). DevOps & MLOps: Docker:Proficiency in containerization - building, managing, and deploying Docker images and containers. GitLab:Proficient GitLab skills for version control, merge request workflows, and repository management. API Development:Experience withFastAPI, including request validation, async handling, and integration with ML model serving. Broader software development experience expected. At least B2 level of English. Soft Skills: Excellent communication skills Strong work ethic and high personal accountability Ownership mentality - takes full responsibility for deliverables and outcomes Proactive, self-starting approach to identifying problems and driving project success without waiting for direction.