Job description
Description
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.
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.
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.
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.
