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

Wypoon Technologies

Amsterdam

On-site

EUR 70,000 - 110,000

Full time

9 hours ago

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Benefits offered by this job

Competitive compensation

25 days vacation

Relocation support

30% ruling tax benefit

Travel reimbursement

Top-notch equipment

Professional development

Visa sponsorship for family

Temporary accommodation

Comprehensive relocation assistance

Community & events

Job summary

Wypoon Technologies is seeking a Machine Learning Engineer to design and deploy production-grade AI in Azure cloud. You’ll work on end-to-end ML solutions, from data handling to model deployment and monitoring, spanning classification, NLP, and time-series use cases.

You’ll collaborate with data scientists and engineers, apply feature engineering, and implement MLOps practices with CI/CD, versioning, and observability. Relocation support available for global talent.

Qualifications

Bachelor’s degree in Computer Science, Software Engineering, or related field.
5+ years of professional ML or data science experience.
Strong Python and ML libraries experience (scikit-learn, TensorFlow, PyTorch, XGBoost).
Experience deploying ML models in cloud environments (Azure).
Familiarity with ML pipelines, orchestration, and CI/CD practices.
Experience with Generative AI use cases, LLMs, embeddings, or GPT integrations.
Familiarity with Transformers, LangChain, or RAG architectures.
Exposure to Responsible AI, explainability, or ethical ML practices.
Background in MLOps tooling (MLflow, DVC, Feast).
Experience with data labeling tools or ML observability platforms.
Solid software engineering principles and cloud infrastructure knowledge.
Nice-to-have data lakes, distributed systems, APIs.

Responsibilities

Design and implement ML pipelines in Azure cloud environment.
Develop and deploy models for classification, regression, time series, recommendation, or NLP use cases.
Work with structured and unstructured data; apply feature engineering and model tuning.
Package and deploy models using containers (Docker, Kubernetes).
Automate and monitor ML workflows with MLflow, Airflow, or cloud-native tools.
Collaborate with data scientists, engineers, and product teams to translate business problems into ML solutions.
Contribute to MLOps: model versioning, CI/CD for ML, performance monitoring, rollback strategies.

Skills

Python

ML libraries

Azure cloud

MLOps

CI/CD

Generative AI

Docker

Kubernetes

MLflow

Airflow

LangChain

HuggingFace

RAG architectures

Responsible AI

APIs & Data Lakes

Education

Bachelor’s degree in CS/SE or related field

Tools

Docker

Kubernetes

Azure ML

SageMaker/Vertex AI

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 Azure cloud environment
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 Azure cloud platform
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 platforms
Solid 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).
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!