Engineering Manager, Machine Learning Platform

Key Skills

C Programming, C++, Cloud computing, Data science techniques, Java Programming, Machine learning techniques, MATLAB Programming, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

At Lucid, we set out to introduce the most captivating, luxury electric vehicles that elevate the human experience and transcend the perceived limitations of space, performance, and intelligence. Vehicles that are intuitive, liberating, and designed for the future of mobility.

We plan to lead in this new era of luxury electric by returning to the fundamentals of great design – where every decision we make is in service of the individual and environment. Because when you are no longer bound by convention, you are free to define your own experience.

Come work alongside some of the most accomplished minds in the industry. Beyond providing competitive salaries, we’re providing a community for innovators who want to make an immediate and significant impact. If you are driven to create a better, more sustainable future, then this is the right place for you.

We are looking for a Hands-on Engineering Manager, Machine Learning Platform who is looking for a challenge, enjoys thinking big, and looking to make their mark on an extremely fast-growing company. If building large and building fast, working with a young and very talented team of engineers, and collaborating with the brightest mind in the Automotive industry is what you like, Lucid is the best to experience it.

Role

• Engineering Manager, Machine Learning Platform is responsible to build Machine learning Platform and Infrastructure, for both Vehicle and Enterprise data, This hands-on role helps solve real big data problems, which most of the standard tools on the market are not capable of handling. You will be designing solutions, writing codes and automation, defining standards, and establish best practices across the company. 
• Hands-on architecture, design, and development of ML platform, pipelines. 
• Build and grow an amazing team of data engineers with a strong culture of balancing excellence with moving fast.
• Lead and manage the team as a hands-on technical leader. Help the team make key technical decisions, unblock the team, and guide the team on execution. 
• Utilize cutting edge distributed big data technologies such as Docker, Kubernetes, KubeFlow, MLFlow, Spark, Kafka, S3 Data Lake, Parquet, ORC, Presto, Redshift, and Airflow
• Hands-on application development with Scala, Golang or PySpark 
• Develop, communicate, and evangelize the long-term technical vision and roadmap for data storage, ingestion, and retrieval in collaboration with the technical leads
• Drive the technical and strategic vision for our data integration infrastructure in order to meet current and future needs for scale and interoperability
• Partner with data platform and product engineering teams to design warehouse schemas, develop & maintain ETLs, and define data architectures to ensure consistent, seamless tracking, and measurement of key company and product metrics. 
• Partner with other engineering leaders to evolve and improve engineering culture in a high-paced growth environment. 
• Set technical direction, roadmaps and guide evolution of our ML Platform.
• Deployment of large scale ML pipeline using open source technologies such as Kubeflow, MLFlow, Airflow
• Design and build the next generation of ML architecture that will power large-scale data science projects
• Lead projects with hands-on analysis and modeling, drawing from multiple analytical methods to choose the right tool and right level of complexity appropriate for the challenge.
• Perform and streamline continuous model performance monitoring and debugging in production
• Perform research and utilize state-of-the-art and best practices for model compression, quantization and optimization for deployment
• Contribute to the overall architecture, implementation and ongoing maintenance of our codebase
• Optimize the performance and scale our ML Platform and infrastructure to server ever-increasing volume.

Qualifications

• MS. or PhD in Computer Science, or equivalent.
• 7+ years of hands-on experience in ML pipeline, ETL, data modeling processing
• 3+ years of ML/Data engineering management experience working with Big Data
• Expert in KubeFlow, ML Flow, Spark, Kafka, Presto, Kubeflow, Airflow, or similar technologies. 
• Proficiency with machine/deep learning frameworks such as TensorFlow, Keras, Pytorch, Caffe, MXNet, etc
• Experience in creating production level ML models for training, validation, and inference leveraging real-time systems
• Experience with Kubernetes-based ML Architecture. 
• Experiance with HPC platform on AWS.
• Strong knowledge and understanding of machine learning pipelines from standardization, normalization, clustering, modeling, scoring, validation
• Understanding of ETL engineering and tools so you can interface with data integration teams
• Experience with Timeseries data
• Preferred Experience with automotive data
• Experience working with cloud-based accelerated computing, GPU/TPU, CUDA, parallel computing.