Responsibilities
- Lifecycle Contribution: Actively contribute to all phases of the AI/ML development lifecycle, translating business requirements into scalable technical solutions.
- Pipeline Optimization: Analyze, troubleshoot, and optimize existing AI/ML applications to improve throughput, latency, and system performance.
- MLOps & Infrastructure: Design and implement reliable model tracking, testing, and deployment pipelines to ensure stable, reproducible production environments.
- Architecture & Standards: Apply modern software design patterns, coding standards, and testing methodologies to maximize code maintainability and data integrity.
- Cross-Functional Collaboration: Translate complex technical details into clear user stories and documentation, maintaining strong transparency with both technical team members and business stakeholders.
Basic qualifications
- Education & Experience: Master’s or Bachelor’s degree in Computer Science, Machine Learning, or a highly related technical field, backed by extensive commercial engineering experience.
- Programming Mastery: Deep, production-grade proficiency in Python, alongside a solid understanding of software development principles, core algorithms, and data structures.
- Cloud Infrastructure: Solid, hands-on experience with cloud-based development, with a specific focus on Google Cloud Platform (GCP) stacks.
- MLOps & Version Control: Proven experience with version control systems (Git) and building out structured MLOps environments (experiment tracking, continuous delivery for ML).
- AI/ML Core: A robust understanding of mainstream AI/ML algorithms, frameworks, and modern machine learning paradigms.
- Methodologies: Strong familiarity working within structured Agile/Scrum development workflows.
- Problem Solving: Ability to independently navigate high-complexity technical challenges, knowing precisely when to execute solo and when to collaborate or escalate for efficient resolution.
- Communication: Exceptional communication skills in English, with the ability to lead knowledge sharing and maintain architectural clarity across teams.
Benefits
- A dynamic and innovative workplace, driving advancements in cutting-edge robotic technologies
- The opportunity to collaborate with talented cross-functional teams on meaningful and impactful projects
- Competitive compensation and a comprehensive benefits package
- A supportive culture that fosters continuous learning, growth, and professional development
- Flexible hybrid working model for an optimal work-life balance
- 25 days of annual leave to recharge and relax
- An annual wellness allowance of 3,500 SEK to support your health and wellbeing
Tags & focus areas
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