Senior AI/ML Engineer

Job Summary:

The hands-on Senior AI/ML Engineer is responsible for designing and architecting highly scalable ML platforms and solutions for vehicle data, manufacturing, sales, finance, and other critical systems. If you enjoy building large-scale data and ML systems, working with a talented engineering team, and collaborating with some of the brightest minds in automotive technology, Lucid is the place to experience it.

You Will:

As a Senior AI/ML Engineer on the Data Engineering team, you will play a pivotal role in building and scaling Lucid’s machine learning and GenAI capabilities. 

• Design and implement scalable ML platforms and infrastructure, enabling efficient model training, evaluation, deployment, and monitoring across vehicle, manufacturing, and enterprise domains.
• Develop end-to-end ML solutions, leveraging both traditional ML techniques (e.g., classification, regression, time series forecasting) and deep learning (e.g., embeddings, transformers, neural networks).
• Build and optimize Generative AI systems, including Retrieval-Augmented Generation (RAG), prompt engineering, and fine-tuning of large language models (LLMs).
• Collaborate with data engineers, ML engineers, and software teams to productionize ML models, integrating them into APIs and real-time systems with CI/CD, observability, and model versioning.
• Partner with analysts, scientists, and business stakeholders to translate complex use cases into technical designs, leading the development of POCs from concept through deployment.
• Mentor and guide junior engineers, promoting best practices in ML system design, code quality, experimentation, and model governance.
• Stay up to date with emerging trends in AI/ML infrastructure and GenAI, and actively drive the evaluation and adoption of new tools and techniques across the organization.
• Maintain and improve existing ML services, proactively addressing performance, scalability, and reliability in production environments.

You Bring:

Required:

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field.
• 5+ years of robust, hands-on experience in software engineering, ML engineering, or ML platform development.
• 2+ years of experience in areas such as deep learning, LLMs, NLP, speech, conversational AI, ML infrastructure, fine-tuning, and PyTorch model optimization.
• Strong knowledge of traditional ML techniques, including supervised/unsupervised learning, feature engineering, and model evaluation.
• Expert-level proficiency in Python for ML and data workflows; experience with Java, Go, Rust, or C/C++ is a plus.
• Deep experience with Large Language Models (e.g., LLaMA, GPT, Claude, Falcon), including architectural tradeoffs, capabilities, and deployment considerations.
• Hands-on expertise in deep learning frameworks like PyTorch and/or JAX, and tools such as ONNX, Triton, or Torch-TensorRT.
• Proven experience designing and deploying scalable, high-performance AI systems in cloud environments (preferably AWS).
• Familiarity with ML workflow orchestration tools like Airflow, MLflow, SageMaker, or Vertex AI.
• Solid understanding of RAG pipelines, including hybrid search and vector databases (e.g., FAISS, Weaviate, Pinecone).
• Ability to clearly articulate complex technical concepts to both engineering and business stakeholders.

Preferred:

• Experience with model observability, feature stores, and online/offline inference systems.
• Familiarity with MLOps best practices, including monitoring, drift detection, and model governance.
• Track record of mentoring other engineers or contributing to open-source ML/AI projects.
• Experience working in a high-growth or fast-paced tech environment with cross-functional teams.