Machine Learning Engineer – Cloud | MLOps | GenAI (Relocation provided)

Wypoon Technologies

Amsterdam

On-site

EUR 90,000 - 130,000

Full time

5 days ago

Be an early applicant

Get more replies from employers

Send a job-specific resume in minutes.

Benefits offered by this job

Competitive pay

25 days vacation

Permanent contract from day one

Relocation support

30% ruling tax benefits

Travel reimbursement

Equipment provided

Professional development support

Visa sponsorship for family

Temporary housing

Comprehensive relocation assistance

Community & fun

Job summary

Wypoon Technologies is seeking an experienced Machine Learning Engineer to design and deploy production-grade ML solutions in cloud environments for Dutch and international clients.

You’ll work on predictive analytics, real-time recommendations, and Generative AI use cases, collaborating with data scientists and product teams. A strong emphasis on MLOps, scalable pipelines, and modern tech stacks is expected.

Qualifications

5+ years of professional experience.
Advanced English (minimum B2).
A bachelor’s degree in Computer Science, Software Engineering, or related field.
Strong proficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch, XGBoost).
Experience building ML models on Azure, AWS, or GCP.
Familiarity with ML pipelines, CI/CD for ML.
Experience with Generative AI use cases (LLMs, embeddings, prompt engineering).
Familiarity with HuggingFace Transformers, LangChain, or RAG.
Exposure to Responsible AI/ethical ML practices.
MLOps tooling experience: MLflow, DVC, Tecton, Feast.
Experience with APIs, data lakes, distributed systems; Agile teamwork.

Responsibilities

Designing and implementing ML pipelines in cloud environments (Azure, AWS, GCP).
Developing and deploying models for classification, regression, time series, recommendation, or NLP use cases.
Working with structured and unstructured data; feature engineering and model evaluation.
Packaging and deploying models using Docker and Kubernetes.
Automating and monitoring ML workflows with MLflow, Airflow, or cloud-native tools.
Collaborating with data scientists, engineers, and product teams to translate business problems into ML solutions.
Contributing to MLOps practices: model versioning, CI/CD for ML, monitoring, and rollback strategies.

Skills

Python ML

Cloud platforms

MLOps

Generative AI

LLMs

HuggingFace

Docker Kubernetes

Data pipelines

CI/CD for ML

Agile teams

Education

Bachelor's in CS

Tools

MLflow

DVC

Feast

Tecton

LangChain

RAG

Job description

Are you a Machine Learning Engineer with a passion for building real-world, production-grade AI solutions in the cloud?

At Wypoon Technologies, we’re expanding our network of skilled ML Engineers to support leading clients across the Netherlands. From predictive analytics to real-time recommendations and Generative AI use cases,you’ll work on meaningful projects that scale.

Whether your focus lies in model development, MLOps, or cloud-native architecture, we’re looking for engineers who can bring machine learning to life in enterprise environments.

Why Join Us?

At Wypoon Technologies, you’ll work on dynamic projects for industry leaders such as Heineken, ING, ASML, Philips, and Shell, tackling exciting challenges and delivering tailored enterprise solutions.

Here’s what makes us stand out:

Impactful Work: Shape the future of our clients’ digital landscapes.
Innovative Environment: Collaborate within a supportive team that values learning and growth.
State-of-the-art technology: Access the latest tools and platforms.
Global Opportunities: Dreaming of living and working in the Netherlands or Belgium? We provide full support with visa processes, making your transition smooth and hassle-free!

Key Responsibilities

Designing and implementing machine learning pipelines in cloud environments (Azure, AWS, or GCP)
Developing and deploying models for classification, regression, time series, recommendation, or NLP use cases
Working with structured and unstructured data, and applying feature engineering, model tuning, and evaluation techniques
Packaging and deploying models using containerization (e.g., Docker, Kubernetes)
Automating and monitoring ML workflows using MLflow, Airflow, or cloud-native tools (SageMaker, Vertex AI, Azure ML)
Collaborating with data scientists, engineers, and product teams to translate business problems into ML solutions
Contributing to MLOps practices: model versioning, CI/CD for ML, performance monitoring, and rollback strategies

Requirements

At least 5 years of professional experience.
Advanced proficiency in English (minimum B2 level in speaking, writing, listening, and reading).
A bachelor’s degree in Computer Science, Software Engineering, or a related field.
Strong proficiency in Python, including libraries such as scikit-learn, TensorFlow, PyTorch, or XGBoost
Experience building and deploying ML models in at least one major cloud platform: Azure, AWS, or GCP
Familiarity with ML pipeline orchestration and CI/CD practices
Experience with Generative AI use cases, such as working with LLMs, embedding models, prompt engineering, or custom GPT integrations
Familiarity with HuggingFace Transformers, LangChain, or RAG architectures
Exposure to Responsible AI, explainability, or ethical ML practices
Background in MLOps tooling: MLflow, DVC, Tecton, Feast
Experience with data labeling tools or ML observability platformsSolid understanding of software engineering principles and cloud infrastructure
Experience working with APIs, data lakes, and distributed systems is a plus
Comfortable in Agile environments and cross-functional teams

What We Offer

Competitive Compensation: Salary tailored to your skills and experience.
Generous Time Off: 25 paid vacation days (based on a 40-hour work week).
Job Security: A direct and permanent contract from day one!
Relocation Support: A relocation and travel budget to ease your transition.
Tax Benefits: Eligibility for the 30% ruling.
Travel Reimbursement: We've got your daily commute covered.
Top-Notch Equipment: A high-quality device to ensure you work efficiently.
Professional Development: Financial support for certifications, technical training, and language courses—because we value your long-term career growth.
Family: Visa sponsorship for your partner and children under 18.
Temporary Accommodation: Stay in temporary housing while we help you find your permanent home.
Comprehensive Relocation Assistance: Extensive support to help you settle in smoothly.
Community & Fun: Enjoy team events and connect with developers from around the globe!