Virtusa is seeking a highly technical Deep Learning Senior Engineer (T3) to join our AI delivery hub in Poland. In this role, you will be a primary architect and builder of advanced Generative AI solutions, moving past basic wrappers to design sophisticated Deep Learning architectures. You will specialize in Transformer-based models, RAG systems, and LLM orchestration, specifically leveraging the Google Gemini ecosystem on Vertex AI. This is a high-impact role requiring a blend of scientific rigor and production-grade engineering to deliver state-of-the-art AI applications for our global enterprise clients.
Key Responsibilities:
Model Architecture & Design: Design and implement high-performance Generative AI applications utilizing Transformers, Diffusion models, and advanced NLP techniques.
LLM Orchestration: Build and manage complex, agent-based workflows using frameworks like LangChain and LlamaIndex to automate multi-step reasoning tasks.
Advanced RAG Systems: Architect end-to-end Retrieval-Augmented Generation (RAG) pipelines, integrating enterprise data with Vector Databases (Pinecone, FAISS, Weaviate) while ensuring high semantic relevance.
Google GenAI Mastery: Lead the implementation of Google Gemini models within the Vertex AI platform, optimizing for latency, throughput, and cost.
Fine-tuning & Optimization: Perform model fine-tuning, quantization, and embedding optimization to tailor LLMs to specific domain requirements and enterprise datasets.
Prompt Engineering & Evaluation: Design sophisticated prompt strategies and implement rigorous evaluation frameworks (e.g., RAGAS) to track model accuracy, hallucination rates, and drift.
Deployment & Scaling: Collaborate with MLOps teams to deploy models into production environments using Docker and Kubernetes, ensuring scalability and fault tolerance.
Requirements
6–8 years of experience in Software Engineering or Machine Learning, with a minimum of 3 years focused on Deep Learning and NLP.
Expert-level Python skills, including deep proficiency with scientific and AI libraries (NumPy, Pandas, PyTorch, or TensorFlow).
Strong theoretical and practical understanding of Transformers, attention mechanisms, and semantic embeddings.
Proven track record of building production-ready applications with LangChain, LlamaIndex, and LLM APIs (OpenAI, Anthropic, or Vertex AI).
Hands-on experience with FAISS, Pinecone, or Weaviate, including indexing strategies, metadata filtering, and hybrid search optimization.
Advanced experience with GCP, specifically Vertex AI (Model Garden, Pipelines, and Notebooks) and Cloud Storage.
Deep understanding of NLP concepts such as tokenization, named entity recognition (NER), and semantic search logic.
Experience using RAGAS or similar tools to quantify model performance (precision, recall, faithfulness).
Practical knowledge of Docker and Kubernetes; familiarity with CI/CD for ML models and automated deployment workflows.
Experience building scalable REST/GraphQL APIs and microservices for AI-driven applications.
Understanding of Responsible AI practices, including data privacy (GDPR), PII masking, and bias detection in LLM outputs.
Strong analytical problem-solving skills and the ability to work in an Agile (Jira) environment.
Professional English (C1) is mandatory for collaboration with our international technical leadership.
Bachelor’s or Master’s degree in Computer Science, AI, Mathematics, or a related quantitative field.
Benefits
Fully remote work model
Professional training programs – including Udemy and other development plans
Work with a team that’s recognized for its excellence. We’ve been featured in the Deloitte Technology Fast 50 & FT 1000 rankings. We’ve also received the Great Place To Work® certification for five years in a row
Questions? Get in touch with the recruitment person hiring for this position!
Ready to apply? Check out our recruitment process*
* Please Note: different job opportunities may have a slightly different version of this process.
Follow us and keep up with our latest opportunities!
