ML Ops Engineer: AI & NLP Systems Specialist

Aimlroles; Sant Cugat del Vallès; On-site; EUR 70,000 - 110,000; Full time

Job summary

Aimlroles in Spain is seeking an ML Ops Engineer to apply advanced AI techniques—including machine learning and natural language processing—to solve complex problems and design novel algorithms. Leads independent research, develops systems for tasks like translation and sentiment analysis, and optimizes predictive models.

The role requires delivering robust ML pipelines, documenting findings, and collaborating with teams while managing projects with limited supervision.

Qualifications

• 407 years of experience in AI/ML/NLP roles.
• Bachelor2tb in engineering, computer science, information technology or a related field.

Responsibilities

• Solve difficult and sometimes complex problems using advanced AI technologies such as ML and NLP.
• Conduct experimental research independently with limited supervision to advance AI.
• Apply seasoned professional expertise to resolve a wide range of issues creatively.
• Analyze situations or data requiring new perspectives on existing solutions.
• Lead the design and implementation of novel algorithms and AI solutions.
• Develop systems for complex tasks like language translation, sentiment analysis, and speech recognition.
• Implement and optimize algorithms for machine learning and predictive analytics.
• Document and share research processes and findings within the team.
• Manage projects and processes independently with limited supervision.
• Demonstrate good judgment in selecting methods and techniques for obtaining solutions.

Skills

Python

Machine Learning

Natural Language Processing

Data Engineering

MLOps

Cloud Platforms

Generative AI & LLMs

AI Ethics

Statistical Modeling

Critical Thinking

AI agents - agentic systems

Product Thinking

Collaboration & Communication

Education

Bachelore2tbbelo?

Job description

Aimlroles in Spain is seeking an ML Ops Engineer to apply advanced AI techniques—including machine learning and natural language processing—to solve complex problems and design novel algorithms. Leads independent research, develops systems for tasks like translation and sentiment analysis, and optimizes predictive models.

The role requires delivering robust ML pipelines, documenting findings, and collaborating with teams while managing projects with limited supervision.