Lucid Reality Labs is pioneering the development of next-generation XR solutions that transform how people interact, learn, and solve challenges in a rapidly evolving world. Our mission is to deliver cutting-edge technologies that redefine user experiences while addressing real-world needs.
This is a great opportunity to join the key team, gain hands-on experience and exposure to spatial computing technology, and contribute to our Mission by disrupting global challenges with responsible technology!
At the moment we are looking for a Machine Learning Engineer to research, develop, and implement machine learning models, particularly focusing on large language models customization.
Responsibilities:
- Design, develop, and maintain advanced neural network architectures using TensorFlow.
- Research and experiment with emerging techniques to enhance model performance, reduce latency, and optimize resource usage, including fine-tuning large language models.
- Convert TensorFlow models to TensorFlow Lite or other mobile-friendly formats.
- Ensure efficient performance on mobile devices by regularly testing and fine-tuning models across various hardware platforms.
- Continuously optimize and fine-tune models to meet performance, latency, and resource requirements.
- Collaborate with engineering teams to implement best practices in containerization, monitoring, and scaling.
- Partner with cross-functional teams (e.g., product, research) to identify new use cases for LLM-based solutions.
- Present technical findings and recommendations to both technical and non-technical stakeholders.
- Keeping abreast of the latest developments in machine learning, TensorFlow, mobile ML deployment and large language model advancements.
Requirements:
- Bachelor’s degree in Computer Science, Mathematics, or a related field (Master’s is a plus).
- Proven experience as a Machine Learning Engineer or in a similar role.
- Strong foundation in data structures, mathematics, algorithms, probability, statistics, and software architecture.
- Experience building and optimizing various neural architectures
- Familiarity with LLM fine-tuning, prompt engineering, and inference optimization.
- Ability to write robust code in Python. Python proficiency is especially important.
- ML Frameworks & Libraries: TensorFlow, Keras, PyTorch, scikit-learn, etc.
- Knowledge or hands-on experience with reinforcement learning to the requirements and its practical applications.
- Experience working with databases (e.g., SQL, NoSQL) for data storage, retrieval, and management.
- Proficient with Git and ML-specific version control solutions (DVC, MLflow).
- Ability to prepare comprehensive documentation for models, algorithms, and experiments.
- Skilled at conveying complex technical topics to both technical and non-technical audiences.
- Experience working with Generative AI frameworks such as Langchain, Hugging Face Transformers, LlamaIndex, etc.
- Experience with vector search systems, knowledge graphs, and RAG architecture
- Hands-on experience with deploying models in cloud architectures such as Azure/AWS and containerized platforms like Docker or Kubernetes
- Strong understanding of privacy and data security principles when handling sensitive data in LLM applications.
- Experience implementing security guardrails for generative AI systems, such as data anonymization, encryption, and access control mechanisms
Will be a plus:
- Knowledge of other programming languages such as C++ or Java.
- Experience developing Computer Vision machine learning models.
- Experience with TensorFlow Lite or other tools for deploying machine learning models on mobile devices.
- Familiar with AI Agent frameworks and development.
Soft Skills:
- Problem-solving
- Critical thinking
- Adaptability
- Attention to detail
- Collaboration
- Proactivity
- Autonomy
What we offer:
- 24 working days paid vacation, 7 days sick leave, and public holidays;
- Flexible working hours of remote work;
- Open-minded and outside-the-box ideas embodied in life;
- Award-winning and diverse team to grow together;
- Access to the newest XR technologies and devices;
- Minimum bureaucracy and a great working environment.