6 publicaciones de empleo destacadas en data science/mlops engineer (¡Están contratando!)

Senior Data Science Engineer
N-iX —En remoto
- Teletrabajo
- Sistemas ERP
- Inglés
- SQL
Solicitud rápida
2d
Staff ML Engineer
Factorial —Barcelona, Barcelona provincia
- De 77.000 € a 92.000 € al año
- Informática
- Ventas
- Inglés
Solicitud rápida
1d
Senior AI / MLOps Engineer (d/f/m)
TK ELEVATOR IBERICA HOLDING, SL UNIPERSONAL —Madrid, Madrid provincia
- Jornada completa
- Teletrabajo
- Azure
- Informática
- DevOps
- Parking gratuito
2d
Sr. Machine Learning Engineer
Fortra, LLC —España
- Jornada completa
- Teletrabajo
- Doctorado
- Java
- Máster
AI Architect / Senior AI Engineer
Plain Concepts —España
- Jornada completa
- Teletrabajo
- Español
- Azure
- DevOps
- Seguro dental
- Abono gimnasio
Solicitud rápida
AI Engineer Senior
Kairos Digital Solutions —España
- Jornada completa
- Teletrabajo
- Inglés
- Bases de datos
- SQL
- Formación continua
- Seguro médico privado

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Staff ML Engineer
Factorial —Barcelona, Barcelona provincia
On the ML lifecycle side, you'll act as the engineering backbone for our Data Scientists and Analytics team—pairing with them to productionize their models,…
De 77.000 € a 92.000 € al año
Solicitud rápida
1d
Software Engineer - AI driven product
Business Insights —Barcelona, Barcelona provincia
Provide the means and the measures for designing and developing all the quality aspects of a software solution, both functionally and technically, in order to…
Solicitud rápida

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Senior Data Science Engineer

N-iX -
En remoto

Solicitud rápida

Detalles del empleo

Hace 2 días

Cualificaciones

TensorFlow
XML
SAP
Estructura de datos
Gestión en la cadena de suministro
Sistemas ERP
Microsoft SQL Server
NoSQL
Inglés
SQL
Machine learning
Embedded software
REST
Estimación y pronóstico
NLP
SAP S/4HANA
APIs
Escalabilidad
Agile
Cloud
JSON
Manufactura
Requisitos comerciales
Graph databases
Python

Descripción completa del empleo

N-iX is a global software development company founded in 2002, connecting over 2,400+ tech professionals across 40+ countries. We deliver innovative technology solutions in cloud computing, data analytics, AI, embedded software,IoT, and more to global industry leaders and Fortune 500 companies. Join us to create technology that drives real change for businesses and people across the world.

Our client is an innovative technology company developing advanced AI-powered solutions for enterprise and industrial environments. The organization focuses on leveraging artificial intelligence to optimize complex engineering, manufacturing, and supply chain processes through intelligent software platforms and data-driven decision-making.

The role supports two strategic AI initiatives aimed at transforming engineering and supply chain operations. The first program focuses on accelerating systems engineering lifecycles through NLP, Large Language Models, and automated compliance checking of complex technical and regulatory documentation. The second program is dedicated to predictive supply chain intelligence, including demand forecasting, spend analytics, supplier risk assessment, and anomaly detection. The technical environment includes enterprise ERP systems, engineering data models, Data Lakehouse infrastructure, and large-scale AI platforms integrated through RESTful services.

Responsibilities

Design, develop, and deploy production-grade machine learning and AI solutions.
Fine-tune and optimize Large Language Models (LLMs) for domain-specific use cases involving technical and regulatory documentation.
Build NLP pipelines capable of extracting structured rules and business logic from unstructured text sources.
Design and implement Retrieval-Augmented Generation (RAG) architectures for intelligent querying of large technical knowledge bases.
Develop time-series forecasting models for spend prediction, demand planning, and supply chain optimization.
Build machine learning models for supplier risk scoring, anomaly detection, and operational analytics.
Create scalable data extraction, transformation, and feature engineering pipelines from structured and unstructured data sources.
Collaborate with Data Engineers and Backend Engineers to integrate AI models into enterprise applications through RESTful APIs.
Optimize model performance, scalability, and reliability for large-scale processing workloads.
Validate model outputs, analyze model performance, and continuously improve prediction quality and accuracy.
Work closely with Product Managers, Domain Experts, and Engineering teams to ensure business requirements are translated into effective AI solutions.

Requirements

5+ years of commercial experience in Data Science, Machine Learning, or Artificial Intelligence.
Strong programming skills in Python.
Hands-on experience with Pandas, NumPy, Scikit-learn, TensorFlow, and/or PyTorch.
Strong experience with Natural Language Processing and transformer-based architectures such as GPT, BERT, Llama, or similar models.
Experience with prompt engineering, fine-tuning, and implementation of Large Language Models.
Proven experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.
Experience building and deploying machine learning models into production environments.
Strong understanding of supervised and unsupervised machine learning techniques.
Experience developing forecasting, classification, and predictive analytics models.
Solid knowledge of statistics, probability theory, experimentation, and model evaluation methodologies.
Experience working with SQL and/or NoSQL databases.
Familiarity with complex data formats such as JSON and XML.
Understanding of REST APIs and backend integration using frameworks such as Flask or FastAPI.
Ability to quickly understand complex domain-specific terminology and translate business requirements into scalable AI solutions.
Experience working within Agile or Sprint-based delivery environments.
Strong analytical thinking, problem-solving, and communication skills.
Upper-Intermediate or higher English level.

Nice to Have

Experience with SAP S/4HANA or other ERP platforms.
Experience working with Data Lakehouse architectures and large-scale enterprise data environments.
Familiarity with specialized engineering data models or other specialized data structures.
Experience with graph databases or graph-based data modeling.
Knowledge of compliance automation, regulatory interpretation, or document intelligence solutions.
Experience in manufacturing, industrial, supply chain, engineering, or other highly regulated industries.
Exposure to MLOps practices and cloud-based AI/ML platforms.

We offer*:

Flexible working format - remote, office-based or flexible
A competitive salary and good compensation package
Personalized career growth
Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
Active tech communities with regular knowledge sharing
Education reimbursement
Memorable anniversary presents
Corporate events and team buildings
Other location-specific benefits

not applicable for freelancers

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