Generative AI Engineer (ID

Amsterdam - Netherlands

Monthly Salary: Not Disclosed

Experience Required: 4-6years

Posted on: 7 hours ago

Vacancies: 1 Vacancy

Job Summary

As a Generative AI Engineer you will:

Design build and deploy Generative AI models for NLP computer vision and multi-modal use cases.
Research evaluate and integrate state-of-the-art Large Language Models (LLMs) for enterprise applications.
Fine-tune foundation models and implement effective prompt engineering strategies.
Develop and optimize large-scale data pipelines using Azure Databricks and Apache Spark.
Build deploy and monitor ML models using robust MLOps workflows.
Collaborate closely with data scientists solution architects and business stakeholders.
Ensure AI solutions follow data governance security and responsible AI standards.
Continuously optimize model performance scalability and reliability in production environments.

What You Bring to the Table:

4-6 years of hands-on experience in Machine Learning AI or Generative AI roles.
Strong proficiency in Python for ML and data engineering use cases.
Practical experience with Generative AI LLMs and model fine-tuning techniques.
Hands-on exposure to Azure Databricks Spark and distributed data processing.
Experience working with ML frameworks such as TensorFlow PyTorch and Hugging Face.
Solid understanding of Azure cloud services including Data Lake Synapse and Azure ML.
Working experience with CI/CD pipelines MLOps practices and automation.

You Should Possess the Ability to:

Translate business requirements into scalable AI and ML solutions.
Design end-to-end ML pipelines from data ingestion to production deployment.
Optimize model performance for accuracy latency and cost efficiency.
Work effectively with cross-functional technical and non-technical teams.
Implement secure compliant and responsible AI solutions.
Monitor deployed models and handle versioning retraining and performance drift.
Work independently in complex problem-solving environments.
Adapt quickly to evolving AI technologies and enterprise ML standards.

What We Bring to the Table:

Opportunity to work on enterprise-grade Generative AI and LLM use cases.
Exposure to large-scale data processing and cloud-native ML architectures.
A technically strong environment focused on modern MLOps and CI/CD practices.
Collaboration with experienced AI engineers data scientists and architects.

Lets Connect

Want to discuss this opportunity in more detail Feel free to reach out.

Recruiter: Asha Krishnan

Phone:; Extn :132

Email:

LinkedIn: Skills:

As a Generative AI Engineer you will: Design build and deploy Generative AI models for NLP computer vision and multi-modal use cases. Research evaluate and integrate state-of-the-art Large Language Models (LLMs) for enterprise applications. Fine-tune foundation models and implement effective prompt engineering strategies. Develop and optimize large-scale data pipelines using Azure Databricks and Apache Spark. Build deploy and monitor ML models using robust MLOps workflows. Collaborate closely with data scientists solution architects and business stakeholders. Ensure AI solutions follow data governance security and responsible AI standards. Continuously optimize model performance scalability and reliability in production environments. What You Bring to the Table: 4-6 years of hands-on experience in Machine Learning AI or Generative AI roles. Strong proficiency in Python for ML and data engineering use cases. Practical experience with Generative AI LLMs and model fine-tuning techniques. Hands-on exposure to Azure Databricks Spark and distributed data processing. Experience working with ML frameworks such as TensorFlow PyTorch and Hugging Face. Solid understanding of Azure cloud services including Data Lake Synapse and Azure ML. Working experience with CI/CD pipelines MLOps practices and automation. You Should Possess the Ability to: Translate business requirements into scalable AI and ML solutions. Design end-to-end ML pipelines from data ingestion to production deployment. Optimize model performance for accuracy latency and cost efficiency. Work effectively with cross-functional technical and non-technical teams. Implement secure compliant and responsible AI solutions. Monitor deployed models and handle versioning retraining and performance drift. Work independently in complex problem-solving environments. Adapt quickly to evolving AI technologies and enterprise ML standards. What We Bring to the Table: Opportunity to work on enterprise-grade Generative AI and LLM use cases. Exposure to large-scale data processing and cloud-native ML architectures. A technically strong environment focused on modern MLOps and CI/CD practices. Collaboration with experienced AI engineers data scientists and architects. Lets Connect Want to discuss this opportunity in more detail Feel free to reach out. Recruiter: Asha Krishnan Phone:; Extn :132 Email: LinkedIn: