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AI Engineer for Data Automation
1 day ago
At Rillion, we're on a mission to revolutionize the way finance teams manage invoices. As an AI Engineer, you'll play a pivotal role in developing machine learning models that drive AI-powered AP automation.
The right candidate will have hands-on experience with implementing scalable AI/ML solutions in production environments. Proficiency in Python and AI/ML frameworks like PyTorch is essential. Familiarity with cloud environments like Azure, AWS, and GCP, with experience scaling AI solutions, is also required.
You'll collaborate closely with product, engineering, and data teams to integrate AI features into our products. Staying up-to-date with emerging AI technologies and contributing to experimentation and innovation is crucial. Building and maintaining effective AI/ML pipelines and deployment infrastructure is also key.
We offer a dynamic work environment where talented colleagues are ready to support your success in your career path. Enjoy our beautiful office in central Stockholm, with hybrid working model, 2 days per week in the office.
Responsibilities:- Develop and implement scalable AI/ML models that support product objectives.
- Collaborate closely with product, engineering, and data teams to integrate AI features into our products.
- Stay up-to-date with emerging AI technologies and contribute to experimentation and innovation.
- Build and maintain effective AI/ML pipelines and deployment infrastructure.
What You'll Bring:
- 2+ years hands-on experience with putting self-developed machine learning solutions into a production environment.
- High proficiency in Python and AI/ML frameworks, i.e. PyTorch.
- Familiarity with working with containers in a cloud environment like Azure, AWS, and/or GCP, with experience scaling AI solutions in production.
- A curious mindset with strong collaboration skills who is comfortable in environments without clear-cut processes.
- Master's degree in engineering or similar.
- Cloud Ops and IaC tools such as Terraform.
- MLOps best practices and tools like Databricks.
- Knowledge of working with visually rich documents (VRDs) and generative AI.
- Experience working with RAG, LLM evaluation, API-driven microservices, cache management and production-level software.
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