onsite
Staff Artificial Intelligence Research Engineer
Staff Artificial Intelligence Research Engineer
Archer is seeking a Staff Artificial Intelligence Research Engineer to design, implement, and evaluate novel machine learning and deep learning algorithms, focusing on Large Language Models (LLMs) and multimodal architectures. This role involves iterating on AI model development, collaborating with engineers to prototype solutions, and transitioning research into production systems.
About the role
About Archer
Archer is an aerospace company based in San Jose, California building an all-electric vertical takeoff and landing aircraft with a mission to advance the benefits of sustainable air mobility. We are designing, manufacturing, and operating an all-electric aircraft that can carry four passengers while producing minimal noise.
What You’ll Do
- Design, implement, and evaluate novel machine learning and deep learning algorithms, concentrating on Large Language Models (LLMs), automated speech recognition (transcription), and unified multimodal architectures.
- Iterate on AI model development, starting from the data needed for training, architecture, input/output representations, evaluation, and deployment for complex sequence-to-sequence and multimodal tasks.
- Collaborate with other research engineers to prototype and validate complex solutions from academic literature in natural language processing and speech.
- Conduct experiments to benchmark new techniques and evaluate model behavior.
- Develop tools and frameworks to support scalable and reproducible research and development.
- Communicate research findings to leadership in a concise, and convincing manner.
- Stay current with the latest developments in Generative AI and Speech/Language Models and identify relevant innovations.
- Assist in transitioning research prototypes into production-ready systems.
Minimum Requirements
Education
- Minimum Education Requirement: Master’s degree in Artificial Intelligence, Computer Science, Computational Sciences, Machine Learning, Informatics.
- Alternate Education Requirement: PhD in Artificial Intelligence, Computer Science, Computational Sciences, Machine Learning, Informatics.
Experience
- Minimum Experience Requirements: 3 years of experience with developing and supporting production machine learning systems, including model deployment, monitoring, versioning, and retraining, using modern observability and experimentation tools (e.g., Grafana, Prometheus, Statsig); building ML and deep learning models using Python and PyTorch, including NLP tools (e.g., Huggingface, NLTK, spaCy, transformer-based models); with largescale data pipelines using distributed processing frameworks (e.g., Spark, Databricks); and collaborating with cross-functional teams to translate business requirements into ML solutions PLUS 1 year of experience developing computer vision or multimodal ML systems (e.g., OpenCV, YOLO, vision transformers).
- Alternate Experience Requirements: 2 years of experience with developing and supporting production machine learning systems, including model deployment, monitoring, versioning, and retraining, using modern observability and experimentation tools (e.g., Grafana, Prometheus, Statsig); building ML and deep learning models using Python and PyTorch, including NLP tools (e.g., Huggingface, NLTK, spaCy, transformer-based models); with largescale data pipelines using distributed processing frameworks (e.g., Spark, Databricks); and collaborating with cross-functional teams to translate business requirements into ML solutions PLUS 1 year of experience developing computer vision or multimodal ML systems (e.g., OpenCV, YOLO, vision transformers).