обновлено 2 месяца назад
Machine Learning Engineer (Generative AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Machine Learning Engineer (Generative AI) (Python/AWS/Spark): Designing, building, and deploying production-ready machine learning and generative AI solutions for decisioning, analytics, fraud, and identity products with an accent on scalable cloud-native platforms, advanced modeling, and model productization. Focus on prompt engineering, fine-tuning, RAG, model evaluation, distributed data processing, and delivering reliable production code for global product launches and client implementations.
Location: Sofia, Bulgaria; hybrid work
Company
is a global data and technology company providing data, analytics, and software solutions across financial services, healthcare, automotive, agribusiness, insurance, and other markets.
What you will do
- Design, build, prototype, and deploy machine learning and generative AI solutions for decisioning, analytics, fraud, and identity products.
- Package and productize analytics innovations for execution within the Ascend platform and client-facing software.
- Collaborate with Engineering, Research, and Data Science teams on machine learning, dashboarding, ad hoc analysis, and AI applications in AWS cloud-native big data environments.
- Develop models and generative capabilities using prompt engineering, fine-tuning, RAG, and model evaluation frameworks.
- Create production-quality, modular, reproducible code with version control, code reviews, and automated testing.
- Communicate model methodologies, performance, assumptions, and trade-offs to technical and non-technical stakeholders while supporting product launches and client implementations.
Requirements
- 4+ years of experience in AI, data science, or predictive modeling, including complex hands-on analytical and client-focused projects.
- Advanced degree in Machine Learning, Data Science, AI, Computer Science, or a related quantitative field.
- Statistical modeling and programming experience with Python or SAS.
- Experience with AWS distributed computing and large-scale data analysis using Spark, preferably PySpark.
- Experience applying generative AI tools and rapidly prototyping new concepts.
- Background in model risk management, governance processes, regulatory requirements, and LLM developments.
Culture & Benefits
- Professional development programs with online courses, learning materials, and books.
- Social benefits including life insurance, food vouchers, additional health insurance, a monthly flex allowance, internet coverage, corporate discounts, and a Multisport card.
- 25 days of paid vacation, an additional birthday day off, and three extra paid days for social responsibility events.
- Flexible working hours and home office options within the hybrid work arrangement.
- Employee assistance program, Sharesave plan, family-related allowances, and other benefits.
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