We’re looking for a motivated Junior Generative AI Developer to join our newly launched IT Pod project. This is a hands-on individual contributor role where you’ll collaborate with senior engineers to design, implement, and optimize cutting-edge Generative AI solutions. You’ll work with technologies like LLMs (GPT-4, Claude, Gemini), diffusion models, and multimodal systems — all while following ethical AI practices.
1.Model Development & Fine-Tuning
Assist in training and fine-tuning generative models (text, image, code) using PyTorch, TensorFlow, or JAX
Implement RAG (Retrieval-Augmented Generation) pipelines and optimize prompts for specific domains
2. Tooling & Integration
Build applications using LangChain, LlamaIndex, Hugging Face Transformers
Integrate GenAI APIs (OpenAI, Anthropic, Mistral) into enterprise workflows
3. Prompt Engineering
Design and test advanced prompting strategies (few-shot, chain-of-thought, ReAct)
Create reusable prompt templates for workflows like customer support, code generation, and content moderation
4. Evaluation & Optimization
Develop metrics for hallucination reduction, output consistency, and safety alignment
Optimize inference costs using quantization, distillation, or speculative decoding
5. Collaboration
Work with cross-functional teams (product, data, UX) to deploy AI solutions
Document processes and contribute to knowledge-sharing sessions
Education:
Bachelor’s or Master’s in Computer Science, Data Science, or related field
Technical Skills:
Proficiency in Python and familiarity with PyTorch or TensorFlow
Basic understanding of NLP and neural architectures (Transformers, GANs)
Experience with cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML)
Familiarity with prompt engineering tools (LangChain, DSPy, Guidance, LMQL)
Experience with deployment tools (FastAPI, Docker, MLflow)
AI/GenAI Exposure:
Experience with at least two of the following:
Hands-on projects with LLMs or diffusion models
Vector databases (Pinecone, Milvus) and orchestration tools
Fine-tuning LLMs (Llama 2, Mistral) using LoRA, QLoRA, RLHF
Building RAG pipelines with embedding models (BERT, OpenAI)
Developing applications with Stable Diffusion, DALL·E
NLP projects using spaCy or NLTK
Soft Skills:
Strong problem-solving mindset and curiosity about emerging AI trends
Ability to explain technical concepts to non-technical stakeholders
Certifications:
Microsoft Certified: Azure AI Engineer Associate
Google Cloud Professional Machine Learning Engineer
What you can expect from us:
Unique professional and personal development at one of the pioneer companies in professional insurance support.
Ongoing professional training – to onboard you for a good start and your further professional development.
Your own growth training budget - use internal and external development opportunities and take advantage of your own budget.
LUXMED medical cover for you with full dental care, oncological preventive program and additional mental health support with helpline & individual sessions with a therapist.
Flexible work hours (we start between 7:00 and 10:30 am).
8-hour work time with a lunch break already included - spend the rest of the day doing what is important to you as intended in the #2h4Family program.
Private life insurance - 80% of the premium is covered by an employer.
Employee referral program - we appreciate you recommending your friends to join us.
Additional days off - to celebrate your birthday, moreover, if you want to do a volunteering work, feel free to do so with some extra days off.
Integration events - monthly delicious breakfasts, movie nights, board game nights, outdoor events.
Lively and modern office in the City Centre with parking space for employees.
A supportive and friendly atmosphere created by passionate people.
*depending on the type of contract
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