Medior/Senior MLOps Engineer

Coolgradient is a fast-growing green-tech start-up with a clear vision to make our digital footprint more sustainable.

Why?

Every swipe, every like, every TikTok video we upload, every Zoom call we have, every Netflix video we watch, or everything we buy online is all processed and depends on… data centers. However, these data centers consume large amounts of energy due to the underlying technology we use every day all day.

How?

We have developed an AI-based analytics platform that captures the entire data center (DC) infrastructure—"from roof to room"—to bring the whole DC into a more optimal state. This platform saves energy, water, and scope 3 emissions while increasing reliability and sustainability in data centers across countries like Germany, France, the UK, Australia, and The Netherlands.

We are looking for a highly skilled MLOps Engineer with experience in setting up and scaling machine learning operations infrastructure in the cloud.

What you’ll do

As our MLOps Engineer, you will be crucial in developing, deploying, and maintaining machine learning models that perform in production environments using Azure. You will collaborate closely with data scientists, software engineers, and other stakeholders to ensure seamless integration of machine learning solutions into our products and services. As part of this role, you will also be expected to actively contribute to designing our data science platform to develop the best solution to support our AI models. Additionally, you lead troubleshooting and improving our systems, as well as working proactively to identify opportunities for improvement and efficiency. As such, this role represents a unique opportunity to broadly impact our organization and contribute significantly to our technological evolution.

Additionally you will

• Automate and optimize processes for model deployment and scaling to production-grade environments.
• Ensure robustness, reliability, and scalability of machine learning infrastructure and services on Azure.
• Collaborate with cross-functional teams to understand requirements, implement solutions, and address challenges throughout the ML lifecycle.
• Implement best practices for version control, model governance, and compliance in MLOps workflows.
• Stay updated on the latest developments in AI/ML and recommend improvements to enhance our capabilities and efficiency.

Requirements

• Degree in Computer Science, Engineering or a related field.
• 3+ years of proven experience as an MLOps Engineer or similar role, where you’ve single-handedly designed and implemented ample scalable machine learning pipelines for training, validation, and deployment to production.
• Experience with cloud platforms, containerization technologies and automated testing.
• Experience with model interfacing, automated monitoring and automated model retraining.
• Experience with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Prefect, etc.).
• Strong programming skills in languages such as Python, Java, or Scala.
• Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.
• Strong communication skills and ability to effectively convey technical concepts to non-technical stakeholders.
• Pre, when experience with data science development within a SaaS product development environment.
• Pre, when you have a strong understanding of machine learning concepts, algorithms, and frameworks.
• Pre, when you’ve experience with off-line and on-prem model deployment, inference and retraining.

Perks

• Working on making the world of data centers more sustainable
• Enjoy a competitive salary, pension scheme, holiday allowance, and disability insurance.
• Our goal is to increase our impact and grow. We want you to grow with us and offer an Employee Stock Option Plan.
• A hybrid home-office-remote policy with flexible working hours where we value your regular presence to enjoy team dynamics, but we like to support the flexibility that fits your daily rhythm and preference.
• Lots of mobility options, where we provide a public transportation subscription, or company bike, or we’ll reimburse your travels when you prefer to use your own means of mobility.
• Lots of opportunities for professional growth and development.
• Join activities like meetups or (business) events.
• Work abroad with the team, where we combine good weather, a great environment, and good food.
• And above all: a fun and enthusiastic team that values a diverse and transparent culture.

Visa

At our company, we highly appreciate and encourage diversity. We believe it is crucial to achieving success and being the responsible company we want to be. However, our company currently cannot sponsor any work visas.