Machine Learning Solutions Architect
Vor 4 Tagen
We are a cutting-edge machine learning suite developer, tackling significant challenges in predictive AI. Our software, getML, unlocks a 10x speed-up potential and delivers superior predictive performance, enabling efficiency and innovation at scale.
Our diverse team of experts consists of product enthusiasts, software engineering specialists, and machine learning professionals. We value initiative and forward-thinking ideas.
Job DescriptionWe are seeking a Machine Learning Solutions Architect to join our team. The ideal candidate will have experience in data science and software engineering, with a strong background in mathematics and statistics. Proficiency in Python and DevOps practices is required.
- The scope of tasks will depend on clients' and internal challenges. You will support us in specific areas with a high degree of autonomy.
- You will lead and participate in the entire project lifecycle, from business development and pre-sales to implementation, ensuring successful delivery of data, AI, and analytics solutions.
The salary range for this role is **€48,000-80,000 per annum**, plus stock options, depending on the leveling framework. Benefits include flexible work environment, remote work opportunities, wellness and commuting benefits, and more.
Required Skills and QualificationsHere are some qualifications that would help you succeed in this role:
- 3+ years of experience in data science and software engineering, ideally within a consultancy or IT industry setting.
- Strong background in mathematics, physics, or a related field, with a solid understanding of statistics and machine learning concepts.
- Proficiency in Python and DevOps practices, including CI/CD pipelines and containerization.
We offer a range of benefits to support your personal and professional growth:
- Cutting-edge gear: latest hardware, height-adjustable desk, and 40-inch curved screen.
- Wellness and commuting benefits: subsidised lunch, Deutschland Ticket, Urban Sports Club membership.
- Flexible work environment: hybrid office arrangement, flexible working hours.
- Remote work opportunities: work from anywhere for a certain period.
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