Senior MLOps Engineer

Aircall is a place where voices are valued.
Backed by over $220 million of investment since 2015, we create technology that fuels accessible, transparent and collaborative communication to empower our base of 14,000+ customers (and growing) to make authentic, human connections.
Conversation is a cornerstone of our culture. Wherever our people find themselves in the Aircall world – Paris, New York, Sydney, Madrid, London, Berlin, Tel Aviv, or at home – everyone has a voice that is valued.
Whatever your background, wherever you’re from – we want you to join the conversation. Let’s talk.
We are looking for engaged and passionate Senior MLOps Engineer to join our growing Team.
***This position is open to candidates willing to relocate to Madrid***
Your primary responsibility will be to design, develop, and manage MLOps pipelines and infrastructure specialized for voice/text analysis related applications. You will work closely with software engineers, and DevOps teams to ensure the successful deployment, integration and scaling of machine learning models or successfully integrate managed AI services across our products.
Your team will leverage AI to bring value to our 17000+ customers across the world while evangelizing AI usage across our engineering and product teams. Quality, excellence, and agility drive our delivery processes and you will help us level these up.
Using a variety of back-end stacks, appropriate for each requirement, but always hosted on AWS, we build added value and resilient services on top of voice and fully integrate with our customers’ business critical tools (CRM, Helpdesk, E-Commerce, …).

Your mission @ Aircall

• Model Deployment and Scaling: Manage the deployment of machine learning models into production environments, ensuring scalability and reliability to handle large-scale datasets using cloud technologies.
• Automation and CI/CD: Industrialization of model deployment, orchestration and workflows. Establish CI/CD pipelines for efficient model versioning, testing and deployment
• Model Development and Optimization: Collaborate with data scientists and engineers to optimize, and fine-tune machine learning models for voice/text analysis
• Infrastructure Management: Utilize containerization technologies and cloud-based services to set up and manage infrastructure, enabling seamless model deployment and scalability
• Monitoring and Anomaly Detection: Implement monitoring systems to track model performance and identify anomalies
• Security and Compliance: Ensure the security and privacy of our data and models, adhering to relevant data protection regulations and industry best practices
• Collaboration and Communication: Collaborate with all engineering teams to integrate machine learning solutions into existing applications. Effectively communicate technical concepts to non-technical stakeholders.
• Research and Innovation: Stay abreast of the latest advancements in machine learning and MLOps technologies, contributing innovative ideas to enhance our product.
• Involvement in product and platform performance optimization and live site monitoring
• Mentor team members

A little more about you:

• Experience: 3+ years experience with MLOps processes and machine learning models deployment is a must-have. Proven hands-on experience in setting up pipelines with cloud or open source tools (e.g., MLFlow, Argo, Kubeflow) is desirable
• Programming Skills: 5+ years of experience in software engineering. Strong programming skills in Python, Typescript,  Scala, Go, Rust or other languages and experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and libraries (e.g., Dask). 
• Experience in using open source/cloud providers of Natural Language Processing and Large Language Models is desirable
• Cloud and Containerization: Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization tools (Kubernetes)
• Problem-Solving Skills: Strong analytical and problem-solving abilities to address complex voice/text analysis topics
• Communication Skills: Excellent communication and interpersonal skills to collaborate effectively with cross-functional teams and stakeholders
• In-depth understanding of the software development lifecycle, DevOps (build, continuous integration, deployment tools) and best practices

Aircall is constantly moving forward. We’re building new roads to complete our journey, and we’re taking people with us who have the same builder mentality.
Let’s grow together: Aircall is a place for those who dare to be bold and seek responsibility, excellence, and the opportunity to push themselves to new heights.
We’re creating a place where great people trust one another and thrive together.
People flourish at Aircall and now is the time to be part of the team and the journey we’re on.
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