puestos de Analista De Datos en España

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We provide a range of benefits across our locations, including but not limited to:

• We are a remote-first organization and most of our roles are work-from-home.
• 4 additional wellbeing days in addition to existing annual leave allowance.
• Access to learning platforms and dedicated learning & development time.
• A range of wellbeing initiatives, including free online yoga classes and an employee assistance plan.
• Employees can dedicate three days each year to volunteer.

The role: We are looking for a Senior Machine Learning Engineer, who will be responsible for leading the deployment and maintenance of advanced ML models, including large language models (LLMs). This role focuses on enhancing ML operational processes to drive business value using state-of-the-art AI technologies, and on leading projects involving cutting-edge AI techniques to positively impact and achieve portfolio goals.

Responsibilities:

• Designing scalable ML infrastructure, collaborating with the team.
• Adopting MLOps best practices; designing pipelines for training and deploying advanced AI models.
• Identifying and implementing automation opportunities in developing and deploying AI systems.
• Collaborating with stakeholders to align AI models with business requirements.
• Overseeing integration of ML models into production, ensuring efficient serving of AI applications.
• Leading complex ML projects from development to deployment.
• Mentoring junior team members, enforcing best practices in AI model development and deployment.
• Leading process improvement initiatives to optimize workflows for advanced AI projects.

Skills:

• Extensive experience in end-to-end ML projects and deploying production-grade ML models, including LLMs.
• 5+ years of professional experience in ML engineering or related roles.
• Proficiency in Python, ML libraries, and algorithms.
• Expertise in deep learning frameworks; experience with LLMs (e.g., GPT, BERT) and generative models, including prompt engineering and fine-tuning.
• Experience with MLOps tools (e.g., MLflow, TFX, Kubeflow) for managing complex models.
• Proficiency in REST API design in Python (Flask, FastAPI) for serving AI services.
• Experience with cloud platforms (Azure, AWS, or GCP) for model training and deployment.
• Expertise in Docker and Kubernetes for efficient model deployment.
• Experience with workflow engines (e.g., Airflow) for automating data and model pipelines.
• Knowledge of data versioning tools like DVC for reproducibility.
• Familiarity with NLP techniques and frameworks (e.g., Hugging Face Transformers) for LLMs.
• Agile project management methodologies (Scrum, Kanban); experience in agile AI teams.
• Strong communication, problem-solving, leadership, and stakeholder management skills with a continuous learning mindset.

Apply now

Please click the 'apply' button on this page and submit your application in English.

Please inform us if you require any special accommodations to participate fully in our recruitment experience. You can contact us at careers@frontiersin.org for any additional support.

Equal opportunity statement
Frontiers actively embraces diversity and is a safe and welcoming workplace. Recruitment is free from discrimination – including based on race, national or ethnic origin, age, religion, disability, sex, gender identity or sexual orientation. With employees from more than 50 different nations, our diversity creates vibrant teams and constantly challenges us to appreciate multiple perspectives.