Auf einen Blick
- Aufgaben: Design and manage cloud infrastructure for ML models and audio pipelines.
- Arbeitgeber: Join ai|coustics, a Berlin startup revolutionizing Generative Audio AI technology.
- Mitarbeitervorteile: Enjoy competitive pay, stock options, and professional growth in a dynamic startup culture.
- Warum dieser Job: Be part of a groundbreaking team shaping the future of audio technology.
- GewĂĽnschte Qualifikationen: Experience with Docker, Kubernetes, CI/CD pipelines, and cloud services required.
- Andere Informationen: Ideal start date is February 15, 2025.
Das voraussichtliche Gehalt liegt zwischen 48000 - 84000 € pro Jahr.
ai|coustics is a Berlin-based startup pioneering Generative Audio AI technology for speech enhancement. We’re on a mission to redefine how people experience speech quality and intelligibility in real-time communication and media content, serving millions of users across diverse verticals—including TVs, Soundbars, Headphones, Hearing Devices, Broadcasting, Streaming, and more. Our approach goes beyond noise suppression, crafting listening experiences that set new industry standards. If you’re excited about building robust, scalable systems and empowering cutting-edge machine learning, join us at ai|coustics and play a pivotal role in shaping the future of audio technology.
The ideal start date for this position is February 15, 2025.
Tasks
- Build and Maintain Infrastructure : Design, implement, and manage cloud and on-premise infrastructure for training, experimentation, and deployment of ML models and audio pipelines.
- Enable the ML Team : Collaborate closely with data scientists and audio ML engineers to understand their workflows, ensuring they have the necessary tools, environments, and resources to iterate quickly.
- Automate Deployment : Develop and maintain CI/CD pipelines for machine learning and production software services, ensuring reliable and repeatable deployments.
- Orchestrate at Scale : Implement containerization (Docker) and orchestration (Kubernetes or similar) solutions to efficiently manage clusters and GPU resources.
- Monitoring & Observability : Set up logging, monitoring, and alerting frameworks to proactively identify and resolve issues across the entire stack.
- Security & Compliance : Ensure the infrastructure and pipelines meet security best practices and comply with relevant data protection standards.
- Continuous Improvement : Evaluate, implement, and advocate for new tools and best practices to streamline ML workflows, from data ingestion and transformation to model serving.
Requirements
DevOps & Infrastructure Expertise
- Experience with containerization tools (Docker) and orchestration platforms (Kubernetes (preferred), ECS, or similar).
- Proven ability to design and manage CI/CD pipelines (e.g., GitLab CI, GitHub Actions, Jenkins).
- Hands-on experience with Infrastructure as Code (Terraform).
- Strong background in cloud services (AWS, GCP, or Azure), including compute, storage, networking, and security.
- Familiarity with logging and monitoring tools (Prometheus, Grafana).
MLOps & Data Pipelines
- Practical knowledge of modern MLOps concepts: model versioning (W&B, MLflow, DVC, or similar), automated data validation, and data lineage.
- Experience enabling ML teams with scalable GPU resources for training and inference.
- Understanding of distributed training techniques and frameworks (PyTorch (preferred), TensorFlow).
- Knowledge of best practices in data management and data processing pipelines for large-scale machine learning projects.
Software Engineering & Collaboration
- Proficiency in at least one major programming language (Python preferred), with clean, maintainable coding habits.
- Familiarity with modern software development workflows (Git, code reviews, agile methodologies).
- Strong communication skills—able to collaborate with cross-functional teams and clearly articulate technical solutions to diverse stakeholders.
Strong Problem-Solving Mindset
- Ability to troubleshoot complex systems and rapidly diagnose issues.
- Keen sense of ownership, with a drive to continuously improve and optimize performance, reliability, and security.
Benefits
- Competitive Compensation : Enjoy a competitive salary package and additional benefits.
- Stock Options : Early-stage employees receive stock options, enabling you to share in the company’s success.
- Learning Opportunities : Collaborate with a team of accomplished audio and ML experts, with ample room for professional growth.
- Startup Culture : Immerse yourself in a dynamic, fast-paced environment with passionate and collaborative colleagues.
- Professional Growth : Seize the chance to shape your career path as the company expands.
- High Impact : Join a groundbreaking startup at a pivotal growth stage, making a real difference in how people experience audio.
- Contribute to the Future : Help define the landscape of generative audio and speech enhancement technology.
If you\’re driven by building robust systems, enabling cutting-edge ML breakthroughs, and shaping the future of real-time speech enhancement, we’d love to hear from you!
Apply now and become a key player in our mission to deliver world-class audio solutions at ai|coustics.
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Platform Engineer (m/w/d) Arbeitgeber: ai-coustics
Kontaktperson:
ai-coustics HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Platform Engineer (m/w/d)
✨Tip Number 1
Familiarize yourself with the specific tools and technologies mentioned in the job description, such as Docker, Kubernetes, and Terraform. Having hands-on experience with these tools will not only boost your confidence but also demonstrate your readiness to contribute from day one.
✨Tip Number 2
Engage with the audio and machine learning community online. Participate in forums, attend webinars, or join relevant groups on platforms like LinkedIn. This will help you stay updated on industry trends and may even lead to valuable connections that could support your application.
✨Tip Number 3
Prepare to discuss your problem-solving approach during the interview. Be ready to share specific examples of how you've tackled complex systems or optimized performance in previous roles. This will showcase your strong problem-solving mindset, which is crucial for this position.
✨Tip Number 4
Highlight any experience you have working in a startup environment or on cross-functional teams. Emphasizing your adaptability and collaborative skills will resonate well with our dynamic culture at ai|coustics, making you a more attractive candidate.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Platform Engineer (m/w/d)
Tipps für deine Bewerbung 🫡
Understand the Company and Role: Dive deep into ai|coustics' mission and values. Familiarize yourself with their Generative Audio AI technology and how it impacts real-time communication. Tailor your application to reflect your enthusiasm for their innovative approach.
Highlight Relevant Experience: Emphasize your DevOps and infrastructure expertise, particularly with tools like Docker and Kubernetes. Provide specific examples of how you've designed and managed CI/CD pipelines or worked with cloud services like AWS or GCP.
Showcase Problem-Solving Skills: Illustrate your strong problem-solving mindset by sharing instances where you successfully diagnosed and resolved complex system issues. This will demonstrate your ability to thrive in a fast-paced startup environment.
Craft a Compelling Cover Letter: Write a cover letter that not only outlines your qualifications but also conveys your passion for audio technology and machine learning. Make sure to express why you want to join ai|coustics and how you can contribute to their mission.
Wie du dich auf ein Vorstellungsgespräch bei ai-coustics vorbereitest
✨Understand the Company’s Mission
Familiarize yourself with ai|coustics' mission to redefine speech quality and intelligibility. Be prepared to discuss how your skills in building robust systems can contribute to this goal.
✨Showcase Your DevOps Expertise
Highlight your experience with containerization tools like Docker and orchestration platforms such as Kubernetes. Be ready to provide examples of how you've designed and managed CI/CD pipelines in previous roles.
✨Demonstrate Collaboration Skills
Since collaboration with data scientists and audio ML engineers is crucial, prepare to discuss past experiences where you successfully worked in cross-functional teams. Emphasize your communication skills and ability to articulate technical solutions.
✨Prepare for Technical Questions
Expect questions related to MLOps concepts, cloud services, and logging/monitoring tools. Brush up on your knowledge of modern data processing pipelines and be ready to troubleshoot complex systems during the interview.