Senior Machine Learning Operations (MLOps) Engineer
Sinch Sweden AB / Datajobb / Stockholm
2025-08-21
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hela Sverige ABOUT SINCH
Sinch is pioneering the way the world communicates. More than 150,000 businesses - including Google, Uber, Paypal, Visa, Tinder, and many others - rely on Sinch's Customer Communications Cloud to power engaging customer experiences through mobile messaging, voice, and email.
Whether you need to verify users or craft omnichannel campaigns, Sinch makes it easy. Our AI-infused Super Network, APIs, and applications ensure you can connect with your customers reliably and securely, at every step of their journey.
At Sinch we "Dream Big", "Win Together", "Keep it simple", and "Make it Happen". These values are our foundation!
DESCRIPTION
As a Senior Machine Learning Operations (MLOps) Engineer at Sinch, you will be a driving force in designing, developing, and maintaining our cutting-edge AI and Data Science architecture. Your in-depth knowledge will be critical as we enhance our MLOps practices by architecting and implementing robust, automated pipelines for the continuous training, validation, and deployment of our machine learning models. You will be instrumental in productionizing these models at scale, focusing on monitoring, scalability, and reliability across our cloud infrastructure (GCP, AWS). Your expertise will ensure that our ML workflows are reproducible and efficient, leveraging tools like Kubernetes, Docker, and MLFlow to bridge the gap between data science experimentation and enterprise-grade production deployment. You will work independently with minimal guidance, leading efforts in the design of training and deployment pipelines of sophisticated machine learning models. You will also play a pivotal role in facilitating communication between business and engineering teams, ensuring alignment on product strategy and progress.
You will work on the Corporate AI team at Sinch, which is responsible for helping Sinch accelerate and expand company-wide adoption of AI technologies, by consolidating resources, establishing best practices, fostering knowledge-sharing, ensuring ethical and compliant AI practices, and mitigating associated risks.
Tech stack: Python, FastAPI, Terraform, Docker, Kubernetes, GitLab, GCP, AWS, Databricks, PyTorch, MLFlow, OpenSearch, LangChain, OpenAI LLMs, Gemini LLMs, Open-Source LLMs like LLama.
Technical Leadership: Lead the technical vision for our MLOps framework, architecting robust, scalable, and automated pipelines for the entire machine learning lifecycle, from data ingestion and model training to deployment and production monitoring. You will drive innovation in our ML infrastructure, solving complex challenges related to model scalability, reliability, and reproducibility.
Project Leadership: Lead MLOps-focused projects, such as designing and implementing new CI/CD/CT (Continuous Training) pipelines, productionizing novel model architectures, or enhancing our automated monitoring and validation systems.
Development & Quality: Develop, test, and maintain the infrastructure-as-code for our MLOps platform, ensuring the reliability, scalability, and efficiency of our ML operational workflows and automation tools.
Mentorship: Act as the go-to expert for MLOps, mentoring data scientists and engineers on best practices for model deployment, containerization, and production monitoring to foster a culture of operational excellence.
Process Improvement: Continuously identify bottlenecks and drive process improvements in our ML workflows, championing automation to enhance the speed and reliability of model delivery from experimentation to production.
ML Pipeline Automation & Management: Design, build, and manage the automated systems that deploy, monitor, and maintain our ML models in a multi-cloud environment (GCP, AWS), ensuring high availability and performance.
Communication: Act as the central point of contact between Data Science, Engineering, and Operations teams, ensuring seamless model handoffs, clear communication on deployment status, and alignment on production requirements.
REQUIREMENTS
You are an MLOps evangelist who is passionate about building robust, scalable infrastructure to productionize AI/ML models and solve real-world operational challenges.
You have a passion for mentoring and sharing knowledge on MLOps best practices, including automation, infrastructure-as-code, and production monitoring.
You have at least five years of experience in a hands-on engineering role (such as MLOps, DevOps, or Platform Engineering), with a deep understanding of backend systems, cloud infrastructure, and the principles of operationalizing ML models.
You have expert-level knowledge of CI/CD pipelines and experience adapting them for Machine Learning workflows (CI/CD/CT), using tools like GitLab CI, Jenkins, or similar.
You have a proactive, ownership mindset, with a proven ability to architect solutions for complex infrastructure challenges and drive continuous improvement in a production environment.
You have excellent communication skills, with the ability to translate complex infrastructure concepts to both technical and non-technical stakeholders.
You have extensive hands-on experience with cloud infrastructure services (GCP, AWS), including networking, IAM, and compute, and are proficient with Infrastructure as Code (e.g., Terraform).
You are highly proficient in Python, particularly for automation, scripting, and building backend services.
You have deep, production-level experience with Docker and Kubernetes, including designing and managing containerized applications and ML workloads at scale.
You are a proven self-starter who works with minimal guidance and can take full ownership of the MLOps platform and its roadmap.
Our corporate language is English, please submit your application in English.
OUR HIRING PROCESS
We are committed to ensuring a recruitment process that is fair, objective, consistent, and inclusive. Our approach includes structured, competency-based interviews designed to evaluate your skills, experience, and qualifications relevant to the role. At times, we may include a data-driven assessment to enhance our hiring success and identify candidates likely to excel.
We believe in a two-way process and encourage you to ask questions throughout the journey. If this role isn't what you're looking for, please explore the other opportunities listed on our career page:
https://www.sinch.com/careers/. No matter who you are, we hope you find an exciting path forward - hopefully with us!
Så ansöker du Sista dag att ansöka är 2025-09-05
E-post:
helene.lin@sinch.com Omfattning Detta är ett heltidsjobb.
Arbetsgivare Sinch Sweden AB (org.nr 556747-5495)
Lindhagensgatan 112 (
visa karta)
112 51 STOCKHOLM
Jobbnummer 9470119