Senior Machine Learning Engineer

WomenTech Network; Madrid; Presencial; EUR 50.000 - 70.000; Jornada completa

Descripción de la vacante

A global technology provider in Madrid is looking for a Senior Machine Learning Engineer to develop and optimize machine learning pipelines. This role focuses on transforming models into scalable, production-grade AI solutions while collaborating with architects and data scientists. Candidates should have experience in building efficient data and ML processes, showcasing their skills in Python and major ML libraries, as well as familiarity with MLOps frameworks. The company emphasizes diversity and continuous learning.

Servicios

Employee learning programs

Access to certifications

Diversity and inclusion initiatives

Formación

• 3–5 years of experience developing and deploying AI / ML models in production environments.
• Strong proficiency in major ML libraries and frameworks.
• Hands-on experience with CI/CD automation.

Responsabilidades

• Build and optimize end-to-end ML pipelines ensuring scalability and efficiency.
• Collaborate with data scientists to integrate models into enterprise systems.
• Automate the full model lifecycle from data ingestion to deployment.

Conocimientos

Python

TensorFlow

PyTorch

Scikit-learn

XGBoost

MLOps frameworks

Containerization

Data preprocessing

Educación

Bachelor’s or Master’s degree in Computer Engineering, Data Science, Mathematics, Physics

Herramientas

MLflow

Kubeflow

Docker

Kubernetes

Azure ML

Descripción del empleo

Who We Are

At Kyndryl, we design, build, manage and modernize the mission‑critical technology systems that the world depends on every day. So why work at Kyndryl? We are always moving forward – always pushing ourselves to go further in our efforts to build a more equitable, inclusive world for our employees, our customers and our communities.

The Role

We’re looking for exceptional talent to join our AI Agentic Innovation Hub at Kyndryl!

Job Description

As a Senior Machine Learning Engineer at Kyndryl’s AI Innovation Hub, you’ll be part of the team that transforms ideas and models into scalable, production‑grade AI solutions.

Working alongside architects and data scientists, you’ll design and optimize the data and ML pipelines that power intelligent systems across industries. Your mission will be to turn experimental models into efficient, reliable, and maintainable products — bridging the gap between innovation and execution.

You’ll work in an environment where automation, engineering excellence, and curiosity converge, driving the continuous evolution of our AI capabilities. This is a role for those who combine strong technical craftsmanship with a builder’s mindset and a passion for making AI work in the real world.

Your Mission

• Build and optimize end‑to‑end ML pipelines, ensuring scalability, efficiency, and reproducibility.
• Collaborate with data scientists and architects to bring models from prototype to production, integrating them seamlessly into enterprise systems.
• Automate the full model lifecycle— from data ingestion and training to validation, deployment, and monitoring.
• Implement MLOps best practices, ensuring robust CI / CD, testing, and observability across AI workloads.
• Contribute to the Hub’s technical excellence by evaluating emerging tools, frameworks, and methodologies in ML engineering.
• Champion software engineering standards, code quality, and documentation to ensure reliability and maintainability.
• Continuously improve performance, resource efficiency, and operational resilience of deployed models.
• Collaborate with cross‑functional teams to align AI solutions with business goals and enterprise architecture standards.

Who You Are

Essential Qualifications

• 3–5 years of experience developing and deploying AI / ML models in production environments.
• Strong proficiency in Python and major ML libraries (TensorFlow, PyTorch, Scikit‑learn, XGBoost, etc.).
• Hands‑on experience with MLOps frameworks (MLflow, Kubeflow, Airflow, DVC) and CI / CD automation (GitHub Actions, Jenkins, Azure DevOps).
• Experience with containerization and orchestration (Docker, Kubernetes).
• Solid understanding of cloud AI platforms (Azure ML, Vertex AI, SageMaker, OpenShift AI).
• Proven skills in data preprocessing, cleaning, and versioning using DataOps practices.
• Experience monitoring and maintaining models in production (data drift, model drift, retraining, observability).
• Familiarity with relational, NoSQL, and vector databases (SQL, MongoDB, FAISS, Milvus, ChromaDB).
• Understanding of security, compliance, and FinOps principles in large‑scale AI workloads.

Education & Certifications

Bachelor’s or Master’s degree in Computer Engineering, Data Science, Mathematics, Physics, or related field.

Postgraduate studies (Master’s in Artificial Intelligence, Data Science, or Software Engineering) are highly valued.

Certifications included in platforms (Azure, AWS, GCP) or MLOps frameworks are a plus.

Proven commitment to continuous learning and staying up to date with advances in AI engineering and automation.

Preferred Skills

• Experience working with LLMs, RAG architectures, or multi‑agent systems.
• Knowledge of feature engineering, data lineage, and metadata management for ML pipelines.
• Exposure to streaming data and real‑time model serving.
• Understanding of micro‑service‑based architectures and API design for AI integrations.
• Familiarity with observability tools (Prometheus, Grafana).
• Ability to design reusable components and templates for rapid experimentation and deployment.
• Passion for automation, optimization, and reproducibility in ML workflows.

Soft Skills

• Collaborative mindset, working effectively with architects, data scientists, and developers toward shared goals.
• Strong analytical thinking and problem‑solving abilities, balancing rigor with creativity.
• Clear communication, able to explain technical topics to both experts and non‑specialists.
• Attention to detail and dedication to high‑quality, maintainable, and well‑documented code.
• Result‑oriented approach, focused on delivering impactful, production‑ready solutions.
• Curiosity and initiative, continuously exploring new frameworks, methodologies, and emerging AI tools.

Being You

Diversity is a whole lot more than what we look like or where we come from, it’s how we think and who we are. We welcome people of all cultures, backgrounds, and experiences. But we’re not doing it single‑handily: Our Kyndryl Inclusion Networks are only one of many ways we create a workplace where all Kyndryls can find and provide support and advice. This dedication to welcoming everyone into our company means that Kyndryl gives you – and everyone next to you – the ability to bring your whole self to work, individually and collectively, and support the activation of our equitable culture. That’s the Kyndryl Way.

What You Can Expect

With state‑of‑the‑art resources and Fortune 100 clients, every day is an opportunity to innovate, build new capabilities, new relationships, new processes, and new value. Kyndryl cares about your well‑being and prides itself on offering benefits that give you choice, reflect the diversity of our employees and support you and your family through the moments that matter – wherever you are in your life journey. Our employee learning programs give you access to the best learning in the industry to receive certifications, including Microsoft, Google, Amazon, Skillsoft, and many more. Through our company‑wide volunteering and giving platform, you can donate, start fundraisers, volunteer, and search over 2 million non‑profit organizations. At Kyndryl, we invest heavily in you, we want you to succeed so that together, we will all succeed.

Get Referred!

If you know someone that works at Kyndryl, when asked ‘How Did You Hear About Us’ during the application process, select ‘Employee Referral’ and enter your contact's Kyndryl email address.