6 дней назад
Senior AI Engineer (GenAI)
hhВакансия с HeadHunter. Контакт ведёт на hh.ru
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Описание вакансии
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TL;DR
Senior AI Engineer (GenAI) (Generative AI, LLMs, RAG): Designing and deploying generative AI solutions from proof of concept through production, with an accent on data pipelines, model selection, prompt engineering, and evaluation frameworks. Focus on building agent-centric workflows, integrating vector databases and AI models into scalable systems, and optimizing security, latency, cost, and performance.
Location: Remote, hybrid, or onsite in Kazakhstan; offices are available in Astana, Almaty, and Karaganda.
Company
EPAM is a technology and innovation company delivering solutions for leading organizations across multiple industries.
What you will do
- Translate complex business challenges into generative AI solutions across PoC, MVP, and production stages.
- Design data-processing pipelines covering tokenization, text normalization, and document structuring.
- Select, fine-tune, and integrate large language models and other generative AI models through APIs and open-source tools.
- Build RAG pipelines, agent-centric workflows, multi-model systems, prompt strategies, and evaluation frameworks.
- Deploy scalable AI solutions in cloud-native and on-premises environments while balancing cost, performance, and scalability.
- Collaborate with engineers, product managers, clients, and cross-functional teams on adoption, education, security, privacy, and ethical AI practices.
Requirements
- 3+ years of data science experience delivering machine learning solutions end to end, with knowledge of CRISP-DM.
- Strong Python skills and experience with NumPy, pandas, PyTorch or TensorFlow, Hugging Face Transformers, and LangChain.
- Hands-on experience with LLMs, RAG pipelines, NLP, and APIs such as Azure OpenAI or AWS Bedrock.
- Backend development experience with FastAPI or Flask and interactive application development with Streamlit or Gradio.
- Experience deploying models with Docker and MLflow, and using vector databases such as Qdrant, FAISS, or Chroma.
- Knowledge of prompt-injection risks, mitigation strategies, communication with non-technical stakeholders, and cross-functional collaboration.
Nice to have
- Experience with RLHF, multimodal AI, fine-tuning large datasets, knowledge distillation, or quantization.
- Background in human evaluation, annotation workflows, or using LLMs as evaluators.
- Experience onboarding enterprise clients to generative AI platforms.
Culture & Benefits
- Work from home or from an EPAM office, with the opportunity to work abroad for up to two months per year.
- Relocation opportunities within EPAM offices in more than 55 countries.
- Leadership development, career advising, soft-skills and well-being programs.
- Professional certifications, LinkedIn Learning, Get Abstract, and English classes with certified teachers.
- Medical and family care package, six trust days per year, psychology-session coverage, and additional employee benefits.
- Employee Stock Purchase Plan, referral bonuses, corporate events, and social activities.
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