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At Nortal, we believe in building seamless experiences with meaningful impact — whether that means smarter governments, better healthcare, next-gen telecom solutions, or transforming how global enterprises leverage data and AI.
To support our vision, we are building a talent pipeline for future needs and are currently looking for a Senior Data & AI Engineer to join our journey.
Responsibilities
- Design and implement Python-based services that leverage language models (LLMs), voice models, and embedding models to solve real-world business problems.
- Collaborate with cross-functional teams to build scalable, highly available and maintainable solutions.
- Implement data ingestion pipelines to transform unstructured data, such as documents and media.
- Build integration pipelines and connectors to existing systems to retrieve data and authenticate users.
- Evaluate AI-based systems in relation to their use case using metrics such as groundedness, accuracy, relevance, faithfulness, word error rate, etc.
- Integrate machine learning model-based services into CI/CD pipelines.
- Maintain high engineering standards through clean, well-documented, and testable code.
- Stay up to date with advances in generative AI, speech recognition and synthesis, embedding-based retrieval systems, and assess their applicability to different use cases.
- Troubleshoot and optimise deployed services, ensuring resilience and high performance in production environments.
- Implement an observability stack on GenAI applications to monitor costs, latency, performance, and adherence to safety guidelines.
- Guide tool selection and architecture design for AI model deployment and service orchestration.
- Support agile processes (Scrum/Kanban), including sprint planning, code reviews, and retrospectives.
- Participate in internal knowledge sharing, mentoring, and advancing Nortal's Data & AI engineering practices.
- 4+ years of hands-on experience in software engineering, preferably in data- or AI-focused projects.
- Proficient in Python, with experience in building APIs/services that integrate machine learning models.
- Familiarity with ML and DL frameworks, such as PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, Langfuse, LiveKit, etc.
- Understanding of vector databases, embedding models, and retrieval-augmented generation (RAG) pipelines, knowledge of graph databases is a plus.
- Experience with speech/voice models and related libraries/tools is a strong plus.
- Solid knowledge of containerization and orchestration (eg Docker, Kubernetes), cloud platforms (eg AWS, Azure, GCP), and infrastructure-as-code (eg Terraform).
- Working knowledge of SQL/NoSQL, and how to handle unstructured and structured data within ingestion pipelines.
- Familiarity with version control systems such as Git.
- Strong communication skills, both written and spoken, with fluency in English.
- Experience working in distributed teams and collaborating across time zones.
Key Skills
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