Engineer, Machine Learning at Otto Aerospace

, , United States -

Full Time

Start Date

Immediate

Expiry Date

12 May, 26

Salary

0.0

Posted On

11 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, AI, Natural Language Processing, Generative AI, Deep Learning, Python, Java, C++, Data Pipelines, Cloud Computing, SQL, Feature Engineering, ETL Processes, Monitoring Tools, DevOps, Containerization

Industry

Aviation and Aerospace Component Manufacturing

Description

About Otto Aerospace OTTO is developing the world’s first fifth-generation business jet, designed for sustainability through the innovative use of advanced super-laminar aerodynamics and high-precision, net-shaped composites. Flight tests of our technology demonstrator validate a dramatic reduction in fuel burn and allow a sizeable improvement in cabin comfort. Otto Aerospace is designing world-class aircraft from first principles physics and delivering ground-breaking aircraft and economic performance. About the Role Otto Aviation is seeking a dynamic and technically proficient Machine Learning Engineer with software developer experience to join its AI Design and Innovation Lab. In this role, you will contribute to designing and deploying scalable AI/ML solutions, developing efficient infrastructure, and collaborating with teams to address complex problems across various business functions. You will play a critical role in advancing Otto's AI initiatives by building production-grade machine learning systems, optimizing model performance, and supporting innovation in next-generation technologies. What You'll Do Design and Develop AI/ML Solutions Develop and implement models for advanced use cases, such as natural language processing, classification, and recommendation systems Apply state-of-the-art machine learning techniques, including large language models (LLMs), generative AI, focusing on performance optimization and scalability Optimize Infrastructure and Pipelines Design scalable training pipelines and inference systems to handle large-scale data processing Develop and optimize data storage and retrieval systems, such as vector databases, to ensure fast and reliable performance Software Development and Integration Collaborate with the AI Lab and cross‑functional teams to integrate machine learning models into existing systems while contributing to end‑to‑end platforms that combine AI capabilities with intuitive user experiences Implement best practices in DevOps, including CI/CD, containerization, and cloud deployment Monitor and Improve Model Performance Build monitoring tools and evaluation frameworks to track machine learning models in production, ensuring sustained quality, accuracy, compliance, performance, and scalability Collaborate with teams to troubleshoot and resolve performance issues, optimizing for latency and efficiency Contribute to Innovation Support the development of AI-driven automation tools and decision-making systems Participate in exploring and piloting emerging technologies to enhance the Lab’s capabilities Who You Are Hands-on experience in designing, deploying, and maintaining production-grade machine learning systems Proven ability to work with both structured and unstructured data in large-scale environments Strong problem-solving and analytical thinking abilities Excellent communication and collaboration skills to work with cross-functional teams Ability to manage competing priorities and deliver high-quality work within deadlines Mentor team members and contribute to the knowledge-sharing culture within the Lab Education Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field (Master’s preferred) Experience 3+ years of experience in machine learning engineering or software development Required Skills Machine Learning and AI: Experience with LLMs, NLP, generative AI, and advanced deep learning techniques Proficiency in PyTorch, TensorFlow, and distributed training frameworks Infrastructure and Pipelines: Knowledge of scalable data pipelines, inference systems, and cloud computing platforms (e.g., AWS, Google Cloud, Azure) Familiarity with vector databases, ETL pipelines, and real-time processing systems Programming and Development: Proficiency in Python, and experience with Java and C++ for building production-grade systems Experience with software development practices such as version control (Git), containerization (Docker), and API design Data Processing and Analysis: Expertise in feature engineering, ETL processes, and handling large-scale datasets Strong command of SQL and tools for data manipulation and analysis Preferred Skills Familiarity with monitoring tools such as Prometheus, MLflow, and OpenTelemetry Experience in deploying AI systems with Terraform, Kubernetes, or similar DevOps tools Exposure to SaaS platform development or intelligent recommendation systems Where You'll Be ****This is a remote position, with travel to the temporary company headquarters in Ft Worth, TX, 1 week every 4-6 weeks for team collaboration. Once our new plant in Jacksonville, FL is open (in 1-2 years), you'll travel there 1 week every 4-6 weeks. Benefits Otto Aerospace provides a robust benefits package that includes competitive salaries, subsidized medical, dental, and vision coverage, 401(k) opportunities, paid short term disability, voluntary long-term disability and additional term life, with 15 paid days off, 13 paid company holidays, and paid sick leave. Depending on seniority and role, some roles qualify for potential bonuses and stock options. Otto Aerospace is an Equal Opportunity Employer We are committed to diversity, equity, and inclusion in every aspect of our hiring process. All applicants will be considered for employment regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability. We believe that a diverse team brings fresh perspectives, innovative ideas, and greater success. The more inclusive we are, the stronger we become. Applicants must be legally authorized to work in the U.S. #LI-Remote

Responsibilities

The Machine Learning Engineer will design and deploy scalable AI/ML solutions, develop efficient infrastructure, and collaborate with teams to address complex problems. They will also build production-grade machine learning systems and optimize model performance.