11 ΡΠ°ΡΠΎΠ² Π½Π°Π·Π°Π΄
Engineering Manager, AI Engineering (Magnet-Griffeye)
ΠΡΡΡ & Π‘ΠΎΠΏΡΠΎΠ²ΠΎΠ΄
ΠΠ»Ρ ΠΌΡΡΡΠ° Ρ ΡΡΠΎΠΉ Π²Π°ΠΊΠ°Π½ΡΠΈΠ΅ΠΉ Π½ΡΠΆΠ΅Π½ Plus
ΠΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ
Π’Π΅ΠΊΡΡ:
TL;DR
Engineering Manager, AI Engineering (Magnet-Griffeye) (AI/ML): Building AI systems that power digital forensics capabilities and help investigators reduce months of case work to days with an accent on applied machine learning, trusted results, and distributed engineering collaboration. Focus on coaching ML engineers, guiding complex technical trade-offs, shaping scalable engineering practices, and integrating AI-assisted development tools safely.
Location: Gothenburg, Sweden; hybrid workplace
Company
develops digital forensics software and AI systems that help investigators analyze evidence and solve cases more efficiently.
What you will do
- Lead and develop a team of 5β10 ML Engineers working on AI systems for digital forensics.
- Own operational excellence, delivery quality, team autonomy, and continuous improvement of engineering frameworks.
- Partner with Tech Leads on technical direction, risks, trade-offs, and adaptable long-term system design.
- Coach engineers through ambiguous projects, technical decisions, ownership opportunities, and career growth.
- Collaborate with Product, UX, and engineering leadership to align roadmaps, capacity, and user needs.
- Establish effective distributed collaboration and determine where AI-assisted development tools add value or create risk.
Requirements
- 3+ years managing or leading engineering teams, with experience building healthy teams, delivering results, and coaching engineers.
- Hands-on experience building applied AI/ML systems and enough technical depth to evaluate engineering judgment and trade-offs.
- Experience coaching Senior and Staff-level engineers with direct, actionable feedback.
- Strong technical judgment and cross-functional communication with engineers, Product Managers, UX, and leadership.
- Experience working effectively across distributed teams and understanding distributed collaboration practices.
- Bachelorβs degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience.
Nice to have
- Experience in high-stakes domains such as security, healthcare, or legal.
- Experience with AI/ML in on-premises, edge, or air-gapped deployment environments.
- Experience building and operating scalable distributed systems.
- Familiarity with MLOps tools for experiment tracking, model versioning, and CI/CD for ML.
Culture & Benefits
- Values include care, accountability, dedication to customers, integrity, empathy, respect, and continuous evolution.
- Focus on continuous learning, professional development, and an inclusive workforce.
- Work in distributed groups spanning Canada and Sweden, with collaboration across ET/MT and CET coverage.
- Employment offers are contingent on satisfactory completion of a background check.
- Accessible recruitment and workplace accommodations are available upon request.
ΠΡΠ΄ΡΡΠ΅ ΠΎΡΡΠΎΡΠΎΠΆΠ½Ρ: Π΅ΡΠ»ΠΈ ΡΠ°Π±ΠΎΡΠΎΠ΄Π°ΡΠ΅Π»Ρ ΠΏΡΠΎΡΠΈΡ Π²ΠΎΠΉΡΠΈ Π² ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ iCloud/Google, ΠΏΡΠΈΡΠ»Π°ΡΡ ΠΊΠΎΠ΄/ΠΏΠ°ΡΠΎΠ»Ρ, Π·Π°ΠΏΡΡΡΠΈΡΡ ΠΊΠΎΠ΄/ΠΠ, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡΠ΅ ΡΡΠΎΠ³ΠΎ - ΡΡΠΎ ΠΌΠΎΡΠ΅Π½Π½ΠΈΠΊΠΈ. ΠΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎ ΠΆΠΌΠΈΡΠ΅ "ΠΠΎΠΆΠ°Π»ΠΎΠ²Π°ΡΡΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡΠΈΡΠ΅ Π² ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΡ. ΠΠΎΠ΄ΡΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β
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