Deep Learning Senior Engineer

This is a remote position. 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 • Professional training programs  • 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