1 001 – 5 000 Darbuotojai
Kvalifikuoto darbuotojo vizos rėmėjas„Euromonitor International“ yra 1972 m. įkurta veiklą vykdanti įmonė, kurioje dirba 1 001–5 000 darbuotojų. Jos darbuotojų samdymo profilis rodo, kad įmonė remia kvalifikuotų darbuotojų įdarbinimą, todėl ji gali būti aktuali specialistams, ieškantiems karjeros galimybių pas patyrusį tarptautinį darbdavį.
Senior Software Engineer, Data Science and AI
Build reusable ranking, retrieval, and evaluation services for Euromonitor’s AI platform. Help product teams across its global market research and data analytics business deliver AI capabilities.
Aprašymas
- Create reusable ranking, personalisation, and recommendation components, from experiments through shared services, with measurable quality baselines.
- Build and run a shared evaluation harness with curated golden datasets, LLM-as-judge pipelines, CI regression gates, and quality metrics.
- Improve retrieval across structured and unstructured data using chunking and indexing strategies, hybrid search, reranking, and embedding lifecycle management.
- Use rigorous statistical methods to design experiments, calibrate judges, and interpret changes in quality.
- Design and build backend services and APIs for retrieval, ranking, evaluation, and agentic AI platform components.
- Contribute to the agent framework, skills, and tool registry, maintaining clean SDK interfaces, backward compatibility, and disciplined abstractions.
- Build observability, cost and token telemetry, quality gates, and Responsible AI controls into production components.
- Help consuming teams adopt the platform through reference implementations, documentation, and established development patterns.
- Work with Engineering, Architecture, and Data Platform teams to align the platform with cloud-native practices.
- Strengthen engineering practices through design reviews, testing standards, and mentoring.
- Report to the Technical Lead as part of the AI and Data Science team based in Bengaluru.
Reikalavimai
- At least 7 years of experience spanning Data Science and software engineering.
- Strong applied Data Science skills, including Machine Learning fundamentals, experience with ranking, recommendation, or NLP, and the statistical grounding to design and interpret evaluations.
- Demonstrated experience building AI and Data Science capabilities as reusable services, libraries, or components adopted by multiple teams.
- Hands-on Generative AI engineering experience with RAG and retrieval systems, plus orchestration frameworks such as LangGraph, LangChain, LlamaIndex, or Semantic Kernel.
- Experience using prompt and evaluation tools.
- Experience with vector or hybrid search technologies such as Elasticsearch, OpenSearch, Azure AI Search, pgvector, or a dedicated vector database.
- Strong backend engineering skills in API and service design, data pipelines, and production operations on Azure, AWS, or GCP.
- Experience with Kubernetes container orchestration.
- Strong Python skills and working proficiency in at least one additional backend language, such as C#, Java, Go, or TypeScript.
- Production engineering discipline, including observability and tracing for LLM workloads, automated testing, CI/CD, and cost awareness.
- Ability to clearly explain technical approaches, trade-offs, limitations, and results to engineers, product owners, and other stakeholders.
- Experience with MCP or tool-calling protocols, agent runtimes, or LLM gateway patterns such as routing, caching, and fallback.
- Experience calibrating LLM-as-judge systems, using golden dataset methods, or running online experiments.
- Experience with evaluation frameworks such as Ragas, DeepEval, or promptfoo.
- Model development experience with PyTorch, TensorFlow, or scikit-learn, including training or fine-tuning beyond API-level use of foundation models.
- Familiarity with AutoGen, CrewAI, OpenAI Agents SDK, MLflow, Azure Machine Learning, SageMaker, or Vertex AI.
- Contributions to internal platforms, open-source libraries, or SDKs with external users.
- Experience in information retrieval or search relevance at scale.
- Background in market research, publishing, information services, or another domain where accuracy is critical.
Privalumai
- Flexible working hours.
- Regular social events, including after-work gatherings and summer and Christmas parties.
- Two volunteering days each year.
- Donations for new starters and support for local and international charities through various initiatives.
- Competitive salaries.
- Private health insurance.
- Generous holiday allowance.
- Extensive training and development opportunities.
- Opportunities for promotion within and across departments.
- Rewards for talented employees.
- Equal employment opportunities and a commitment to non-discrimination.