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Deeplight

Coherent, compact lasers for space LiDAR

Senior Full Stack AI Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeAbu Dhabi - United Arab EmiratesIn-person

About the Job

Requirements

  • Extensive experience designing, launching, and managing containerized AI/ML or data-intensive applications in highly regulated enterprise environments.
  • A proven track record applying deep learning models across both Natural Language Processing and Computer Vision fields.
  • Practical experience implementing production-grade model monitoring frameworks and optimizing complex cloud and token expenditure.
  • Deep operational command of Docker and enterprise Kubernetes infrastructure for running distributed AI applications.
  • Expert-level knowledge of Azure or alternative major clouds, alongside a strong architectural grasp of on-premise deployment constraints, data security, and network topologies.
  • Strong proficiency in Big Data toolsets and modern API gateway designs.
  • A rigorous foundational grasp of transformer architectures, embedding mechanics, and deep learning implementations via PyTorch and TensorFlow.
  • High proficiency across SQL, NoSQL, and Vector Database engines.
  • High proficiency in Python and advanced data processing techniques.

Responsibilities

  • Architect end-to-end, highly secure AI and Generative AI systems capable of running across secure on-premise data centers and public cloud infrastructures such as Azure and AWS.
  • Design, build, and optimize high-throughput, secure APIs to serve complex AI models and agentic workflows to consuming client applications.
  • Integrate proprietary cloud foundation models such as GPT, Claude, and Gemini, and fine-tuned open-source models into unified software ecosystems.
  • Use Transformers, PyTorch, and TensorFlow to implement, evaluate, and optimize deep learning models across NLP and Computer Vision domains.
  • Design scalable knowledge retrieval frameworks using embedding models and enterprise-grade Vector Databases such as Azure DocumentDB, Elasticsearch, and Faiss.
  • Build and evaluate systematic prompting frameworks and compile complex models using ONNX for optimized, low-latency production inference.
  • Own containerization and scaling of AI services using Docker and Kubernetes clusters across development and production environments.
  • Build and automate MLOps continuous integration and deployment pipelines to track model lineage, versions, evaluations, and production drift.
  • Implement FinOps practices to track, monitor, and optimize token usage, cloud compute consumption, and inferencing costs.
  • Architect and optimize large-scale data processing systems using modern Big Data tools to feed raw information into AI training and embedding workflows.
  • Build trust with clients, explain the rationale behind technical decisions, and present and advocate for technical solutions to high-level stakeholders.

Desired Qualifications

  • An MSc or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a highly relevant quantitative discipline.
  • Deep domain experience within banking, including understanding strict data residency laws, financial compliance protocols, and legacy core banking interactions.
  • Practical experience with agentic frameworks such as LangChain, LlamaIndex, and AutoGen, and modern cloud MLOps suites such as Azure AI Studio and Kubeflow.

About the Company

Deeplight

Coherent, compact lasers for space LiDAR

DeepLight develops highly coherent, compact lasers tailored for space research and laser technology applications. Its lasers span the visible and near-infrared spectrum and feature exceptional frequency agility to support advanced applications, including long-range coherent LiDAR. The products rely on a combination of compact light sources and integrated photonics, including MEMS-based ultrafast acousto-optic modulation, enabling fast, precise control of laser light. Unlike many competitors, DeepLight emphasizes tight coherence, high linearity, and integration with MEMS for rapid modulation, supported by collaborations with major space agencies like the European Space Agency and revenue streams from technology sales and tech-transfer funding. The company's goal is to commercialize its laser technology for space research, communication protocols, and fibre sensing, accelerating the deployment of next-generation laser sources in science and industry.

Company size
11-50
Company stage
Debt Financing
Total funding
$90K
Headquarters
Saint-Sulpice, Switzerland
Founded
2021

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