Job
- Level
- Experienced
- Job Field
- IT, Data, DevOps
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Vienna
- Working Model
- Hybrid, Onsite
Job Summary
In this role you build and operate the ML platform for on-device models: implement scalable data and training pipelines, automate CI/CD, quantization and testing, and manage deployments, monitoring and optimization.
Job Technologies
Your role in the team
- In this role, you will be supporting the development of cutting edge machine learning technologies for the next generation of Spectacles.
- Working from our Vienna office, you will be collaborating with other machine learning, computer vision and software teams of Spectacles teams around the world.
- Own the ML platform to support the training, evaluation and deployment of cutting edge ML models for on-device applications.
- Build data and training pipelines at scale.
- Apply strong software engineering to deliver scalable, reproducible end-to-end ML workflows for deep learning and computer vision.
- Develop optimization and release toolchain for automated testing/validation, CI/CD for ML, quantization/distillation and packaging.
- Drive operational excellence by advocating and applying best practices for scalability and cost management.
- Work together with our cross-functional engineering and research teams in computer vision and machine learning.
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Our expectations of you
Education
- Bachelors’ degree in a technical field such as computer science or equivalent experience.
Qualifications
- Excellent software design, development and debugging skills in the context of ML systems.
- Proven track record of developing highly available systems which deal with large amounts of data.
- Working knowledge of ML fundamentals.
- Strong communications and interpersonal skills.
- A genuine passion for learning new things and helping colleagues improve.
- Ability to travel as needed.
- Vertrautheit mit Metaflow, Airflow, Kubeflow oder einem ähnlichen Workflow-Orchestrierungsframework.
Experience
- 4+ years of relevant industry experience.
- Experience with Python, C++ or equivalent combined with a proven track record of learning on the job.
- Experience with machine learning platforms and infrastructure.
- Experience building large scale production machine learning systems or data pipelines.
- Experience with Docker, Kubernetes, Istio/Envoy, NoSQL solutions, Memcache/Redis, Google/AWS services.
- Experience with TensorFlow, PyTorch, or related deep learning frameworks.
- Experienced in MLOps: managing production machine learning lifecycle.
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Description
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Internet, IT, Telecommunication
Dev Reviews
by devworkplaces.com
Total
(1 Review)3.6
Career Growth
3.4Workingconditions
4.6Engineering
2.7Culture
4.0
Machine Learning Platform Engineer
- Location
- Vienna
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
