Machine Learning Engineer
SweedFull Time
Mid-level (3 to 4 years)
Candidates require a Master’s or PhD degree in Computer Science, Computer Engineering, or a related field, and possess familiarity with general AI methodologies/algorithms, and recent LLM technologies, as well as SW techniques for AI quantization, sparsity, model distillation, and the ability to build out RAG systems, develop data pipelines, and build datasets. Strong critical thinking, SW development, and algorithm design skills are also necessary, along with expertise in C++/C, Rust, and Python. Experience with CUDA and familiarity with PyTorch and AI/ML frameworks are considered a plus.
As an AI Systems Engineer, you will design and build end-to-end AI/ML pipelines for model training, evaluation, deployment, and monitoring, developing and maintaining scalable, secure, and fault-tolerant AI infrastructure on cloud and/or on-prem environments, integrating AI/ML models into production systems, collaborating with AI scientists and researcher engineers, implementing automation tools for CI/CD, monitoring and optimizing resource usage and data pipelines, ensuring compliance with data privacy and ethical AI practices, and documenting system architecture and processes to support maintainability and knowledge sharing.
Designs and develops electric vertical takeoff aircraft
Archer designs and develops electric vertical takeoff and landing (eVTOL) aircraft aimed at transforming urban transportation. Their aircraft operate by taking off and landing vertically, which allows them to navigate congested city environments efficiently. Archer targets urban commuters, city planners, and transportation networks, offering eco-friendly solutions to improve urban mobility. Unlike traditional transportation methods, Archer's eVTOLs provide a sustainable alternative that reduces environmental impact. The company generates revenue through the sale of its aircraft and may also offer air taxi services in the future. Archer's goal is to lead the shift towards sustainable air mobility, making urban commuting more efficient and environmentally friendly.