DevOps / MLOps Engineer (m/w/d)
DevOps / MLOps Engineer (m/w/d)

DevOps / MLOps Engineer (m/w/d)

Berlin Vollzeit 48000 - 84000 € / Jahr (geschätzt) Kein Home Office möglich
A

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.
  • Gewünschte 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.

#J-18808-Ljbffr

DevOps / MLOps Engineer (m/w/d) Arbeitgeber: ai|coustics

At ai|coustics, we pride ourselves on being an exceptional employer in the heart of Berlin's vibrant startup scene. Our collaborative and innovative work culture fosters professional growth, allowing you to work alongside industry experts while contributing to groundbreaking audio technology. With competitive compensation, stock options, and a commitment to continuous learning, joining our team means playing a pivotal role in shaping the future of speech enhancement and making a meaningful impact.
A

Kontaktperson:

ai|coustics HR Team

StudySmarter Bewerbungstipps 🤫

So bekommst du den Job: DevOps / MLOps 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 MLOps community online. Participate in forums or attend meetups focused on machine learning operations. This will help you stay updated on best practices and trends, and you might even make connections that could lead to opportunities at ai|coustics.

✨Tip Number 3

Showcase your problem-solving skills by preparing examples of complex systems you've troubleshot in the past. Be ready to discuss these experiences during interviews, as they highlight your ability to handle challenges similar to those you might face at ai|coustics.

✨Tip Number 4

Research ai|coustics and its mission in generative audio AI technology. Understanding the company's goals and how your role as a DevOps/MLOps Engineer fits into their vision will allow you to tailor your conversations and show genuine interest during the application process.

Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: DevOps / MLOps Engineer (m/w/d)

DevOps Expertise
Containerization (Docker)
Kubernetes Orchestration
CI/CD Pipeline Management (GitLab CI, GitHub Actions, Jenkins)
Infrastructure as Code (Terraform)
Cloud Services (AWS, GCP, Azure)
Logging and Monitoring Tools (Prometheus, Grafana)
MLOps Concepts
Model Versioning (W&B, MLflow, DVC)
Data Validation and Data Lineage
Distributed Training Techniques (PyTorch, TensorFlow)
Data Management Best Practices
Proficiency in Python
Modern Software Development Workflows (Git, Agile)
Strong Communication Skills
Problem-Solving Mindset
Ownership and Continuous Improvement

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 experience with DevOps, MLOps, and relevant technologies like Docker, Kubernetes, and CI/CD pipelines. Provide specific examples of projects where you successfully implemented these tools and how they contributed to the team's success.

Showcase Problem-Solving Skills: Illustrate your problem-solving mindset by sharing instances where you diagnosed and resolved complex system issues. Highlight your ability to optimize performance and ensure reliability in your previous roles.

Craft a Strong Cover Letter: Write a compelling cover letter that connects your skills and experiences to the job requirements. Express your passion for audio technology and your eagerness to contribute to ai|coustics' mission. Make sure to convey your collaborative spirit and communication skills.

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 DevOps and MLOps can contribute to this goal.

✨Showcase Your Technical Skills

Be ready to demonstrate your expertise in containerization tools like Docker and orchestration platforms such as Kubernetes. Prepare examples of CI/CD pipelines you've designed and managed, highlighting your hands-on experience with Infrastructure as Code.

✨Collaborate Effectively

Highlight your ability to work closely with cross-functional teams, especially data scientists and audio ML engineers. Share experiences where you enabled teams by providing necessary tools and resources for quick iterations.

✨Problem-Solving Mindset

Prepare to discuss complex systems you've troubleshot in the past. Emphasize your keen sense of ownership and your drive to continuously improve performance, reliability, and security in your projects.

DevOps / MLOps Engineer (m/w/d)
ai|coustics
A
  • DevOps / MLOps Engineer (m/w/d)

    Berlin
    Vollzeit
    48000 - 84000 € / Jahr (geschätzt)

    Bewerbungsfrist: 2027-04-24

  • A

    ai|coustics

    50 - 100
Ähnliche Positionen bei anderen Arbeitgebern
Europas größte Jobbörse für Gen-Z
discover-jobs-cta
Jetzt entdecken
>