Accesa is a leading technology company headquartered in Cluj-Napoca, with offices in Oradea and 20 years of experience in turning business challenges into opportunities and growth.
A value-driven organisation, it has established itself as a partner of choice for major brands in Retail, Manufacturing, Finance, and Banking. It covers the complete digital evolution journey of its customers, from ideation and requirements setup to software development and managed services solutions.
With more than 1,200 IT professionals, Accesa also has a fast-growing footprint, establishing itself as an employer of choice for IT professionals who are passionate about problem-solving through technology. Coming together in strong tech teams with a customer-centric approach, they enable businesses to grow, delivering value for our clients, partners, industry, and community.
Job DescriptionOur client is a trusted partner in the financial-banking sector in Germany, both in the public and private sectors who offers services for over 150,000 banking workstations and for more than 4,500 employees. It covers over 60% of banking sector in Germany.
We are seeking a highly motivated and technically skilled Senior Machine Learning Engineer with a strong focus on Prompt Engineering, Large Language Model (LLM) Evaluation, and Python-based development. This role is central to the enhancement and evaluation of our custom GPT-based systems, contributing directly to innovation in AI-powered solutions.
Responsibilities
Prompt Engineering & Enhancement → Design, extend, and customize system prompts (e.g., chat history, instructions, rules), evaluate the impact of prompt changes, and continuously improve GPT usage scenarios while analyzing the risk-benefit of each modification.
Experimental Feature Development → Conceptualize, prototype, and validate new GPT-based features (e.g., internet search integration, prompt behavior control) to extend system capabilities.
Model Evaluation & Tracking → Evaluate new GPT/LLM releases (e.g., OpenAI models), monitor response quality and consistency, and assess upgrade relevance for various user tiers.
Knowledge Sharing & Research → Stay up to date with the latest techniques in reasoning, chaining, and context optimization, and prepare detailed evaluation reports for the Data Science team.
Python Development & Prototyping → Develop both prototype and production-level code to support AI features, ensuring reliability and maintainability aligned with product requirements.
LLM Integration & Optimization → Utilize frameworks like Langchain to build solutions, implement advanced chatbot capabilities, and contribute to experimental extensions such as tool integration or dynamic content fetching.
Requirements:
- 4+ years of experience with Python and its data science ecosystem (Pandas, NumPy, Scikit-learn), fundamental for data manipulation and modeling
- Proven experience in prompt engineering and LLM behavior analysis.
- Familiarity with LLM integration frameworks such as Langchain or similar.
- Experience in data curation, preprocessing and tokenization for LLM training
- Deep understanding of GPT-based systems and their customization potential.
- Ability to translate product requirements into reliable, maintainable code.
- Experience with experimental feature development and technical feasibility evaluation.
- Excellent documentation and communication skills for sharing findings within a collaborative team.
Nice to have:
- Experience with distributed training
- Experience with MLOps for LLMs
At Accesa you can:
Enjoy our holistic benefits program that covers the four pillars that we believe come together to support our wellbeing, covering social, physical, emotional wellbeing, as well as work-life fusion.
- Physical Wellbeing: Our wellbeing program includes medical benefits, gym support, and personalised fitness options for an active lifestyle, complemented by team events and the Healthy Habits Club.
- Work-Life Fusion: In very dynamic industries such as IT, the line between our professional and personal lives can quickly become blurred. Having a one-size-fits-one approach gives us the flexibility to define the work-life dynamic that works for us.
- Emotional Wellbeing: We believe that to maintain our overall health, we need to invest in our mental wellbeing just as much as we do in our physical health, social connections or in achieving work-life balance.
- Social Wellbeing: As a growing community in a hybrid environment, we want to ensure we remain connected not just by the great work we do every day but through our passions and interests.
