ML/AI Engineer

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.