AI Engineer (m/f/n)

Career at Crowdfox

Your profile

Must-have:

• Proficiency in Python and experience in developing AI projects
• Experience in designing and developing Natural Language Processing (NLP) projects
• Familiarity with frameworks such as PyTorch and LangChain
• Enthusiasm for machine learning and a commitment to continuous learning

Nice-to-have:

• Extensive experience with Large Language Models (LLMs) like GPT-4 and LLaMA
• Strong methodological knowledge in machine learning/deep learning, particularly in NLP
• Knowledge of specific models such as Recurrent Neural Networks, LSTMs, Transformers, and Language Modeling
• Practical experience with frameworks like PyTorch, Hugging Face's Transformers, and OpenAI's Platform
• Proven professional experience in designing and developing NLP projects, including in-depth knowledge of NLP algorithms

Why us?

• Great team with a flat hierarchy, office dogs, and regular events (Crowdfox Days, summer party, and more)
• Regular individual feedback and development discussions, as well as internal communication (intranet, news, etc.)
• Onboarding and professional and personal integration into our teams
• Flexible working hours based on trust, with full-time and part-time options
• Mobile working (Foxtown, home office, from the train, or INSERT YOUR IDEA HERE)
• Permanent contract (PE backed company), attractive and performance-based compensation, company pension plan
• Modern workplace with height-adjustable desks, couch area, cloud-based work via Microsoft 365
• Mediapark in the heart of Cologne, JobRad, JobTicket, free parking, accessibility
• Kitchen & lounge for relaxation, free beverages, many nearby restaurants (meat/veggie/vegan)
• Discount at a nearby premium fitness club

Your mission

• Integration of AI Solutions: Responsible for integrating AI and LLM-based solutions into software projects, working closely with development teams to implement innovative solutions
• Evaluation and Adjustment of Existing AI Models: Lead the evaluation and integration of existing AI models, including fine-tuning and prompt engineering, with a special focus on Large Language Models (LLMs) to support strategic business cases within the company
• Optimization and Innovation: Improve existing algorithms and develop new approaches to continuously enhance the efficiency and effectiveness of AI solutions