Senior AI Engineer (AWS, ML/LLMOps, Generative AI)

EPAM Systems; Deutschland; Vor Ort; EUR 70.000 - 100.000; Vollzeit

Zusammenfassung

EPAM Systems is seeking a highly skilled Senior AI Engineer to lead the development of groundbreaking AI and ML solutions. This role involves designing and implementing AI solutions that meet business requirements, including recommendation systems and data classification.

The ideal candidate will have at least 3 years of experience in AI/ML, be proficient in AWS services, and demonstrate expertise in developing scalable, cloud-based solutions using Python and popular machine learning frameworks.

Qualifikationen

• 3+ years of experience in AI, ML, and MLOps with a strong production-grade portfolio.
• Expertise in AWS services like SageMaker, compute, and storage.
• Proficiency in Python and frameworks such as TensorFlow, PyTorch, and Scikit-learn.

Aufgaben

• Design and implement AI solutions aligned with business needs.
• Build predictive models for customer retention and search optimization.
• Create data aggregation workflows for intelligent insights.

Kenntnisse

AI and ML expertise

AWS tools and services

Python proficiency

ML/LLMOps skills

Recommendation systems knowledge

Advanced SEO techniques

Domain-specific language models

Tools

TensorFlow

PyTorch

Scikit-learn

Jobbeschreibung

We are looking for a highly skilled Senior AI Engineer to spearhead the development of innovative AI and ML solutions, including Recommendation Systems, Data Classification, Search Optimization, and Knowledge Graphs.

Responsibilities

• Design, develop, and implement AI, Generative AI, and ML solutions aligned with business needs
• Build and fine‑tune predictive models for customer retention, search optimization, and specialized language capabilities
• Develop data aggregation, normalization, and enrichment workflows to empower intelligent insights
• Utilize AWS services such as SageMaker, compute, and storage to deploy reliable and scalable cloud infrastructures
• Create and deploy recommendation systems for delivering personalized insights and enhancing user experiences
• Leverage knowledge graphs and entity linking for data enrichment and semantic understanding
• Implement context‑aware AI solutions to deliver enhanced search capabilities based on user intent
• Develop dashboards and scoring mechanisms for decision‑making and user‑focused analytics
• Set up automated alerts and strategies based on machine‑learning risk thresholds
• Collaborate with team members to define research goals and implement intelligent research tools using APIs
• Build and maintain machine‑learning pipelines following ML/LLMOps best practices, including deployment and monitoring
• Apply domain expertise in training models using diverse data sources, both structured and unstructured

Qualifications

• 3+ years of experience in AI, ML, and MLOps, with a track record of developing and deploying production‑grade solutions
• Expertise in AWS tools and services such as SageMaker, compute, and storage
• Proficiency in Python and frameworks such as TensorFlow, PyTorch, and Scikit‑learn
• Skills in ML/LLMOps to implement CI/CD workflows and manage the scalability of deployed models
• Familiarity with recommendation systems, semantic data, and retrieval‑augmented generation (RAG) frameworks such as LangChain or LlamaIndex
• Knowledge of advanced search engine optimization techniques and context‑aware models
• Background in creating domain‑specific language models for high accuracy in specialized research fields
• Understanding of data enrichment techniques, entity linking, and the construction of knowledge graphs
• Capability to implement symbolic AI and domain‑tuned techniques for specialized use cases
• Excellent command of written and spoken English (B2+ level)
• Nice to have: Experience with AWS Lambda and AWS Step Functions for workflow orchestration
• Familiarity with academic and research data trends, discovery methods, and prediction models
• Showcase of building scalable AI‑driven automated systems enhanced by RAG techniques
• Competency in enhancing medical reasoning and crafting intelligent research tools