Overview

BigBear.ai is seeking a Sr Machine Learning Engineer to develop advanced simulation products supporting multiple customers in manufacturing and other market segments.

This position will be based out of Columbia, MD, but is fully remote.

BigBear.AI, a leading artificial intelligence company, seeks a highly skilled Sr Machine Learning Engineer to join our talented team. At BigBear.AI, you will play a key role in developing and implementing cutting-edge machine-learning enhanced applications, contributing to the overall success of our projects. We offer a challenging and rewarding environment where you can make a significant impact and contribute to the next generation of intelligent solutions. We are a leading provider of AI-backed simulation tools that optimize key business processes in the healthcare and manufacturing industries. Our customers include manufacturers, logistics, and supply chain companies as well as hospitals, shipyards. But we plan to go beyond that with your help. As an integral part of our team, you will develop machine-learning techniques for optimization and advanced analysis. The product line focuses on using discrete event simulation to optimize business processes and provide simulation tools for modeling, analyzing courses of action, and supporting planning. This role offers an excellent opportunity to work with a diverse cross-functional team and develop expertise in simulation engine enhancement using machine learning. Here at Bigbear.ai we expect to evolve simulation and define the next level of state of the Art.

If you are passionate about applying your machine learning expertise to solve real-world problems, BigBear.AI offers a challenging and rewarding environment where you can make a significant impact. Join our team and contribute to the next generation of intelligent solutions. Apply now!

What you will do

• Machine Learning Development: Collaborate with cross-functional teams to design, develop, and fine-tune advanced machine learning models and algorithms. This involves both model development and deployment, utilizing modern AI/ML tools and libraries.
• Full Stack Integration: Integrate machine learning solutions into existing systems and services to enhance their functionality and provide insightful predictions. Apply your expertise in machine learning to address complex business problems with innovative solutions.
• Data Pipeline Optimization: Design and optimize data pipelines to support efficient collection, storage, and preprocessing of large-scale datasets. Guarantee data integrity, security, and scalability, and work with these datasets to train and fine-tune machine learning models.
• API Development: Build and maintain RESTful APIs to enable seamless communication between machine learning models and other system components. Collaborate with the team to design and implement efficient API endpoints for data processing and model inference.
• Testing and Debugging: Conduct thorough testing of machine learning models to identify and rectify potential issues related to performance, bias, and underfitting/overfitting. Use best practices for testing, including cross-validation, A/B testing, and confusion matrix analysis.
• Collaboration and Communication: Work closely with a multidisciplinary team of data scientists, software engineers, and product managers. Effectively articulate technical concepts, ideas, and challenges to both technical and non-technical stakeholders.
• Documentation and Maintenance: Create clear and comprehensive technical documentation for developed machine learning models, algorithms, and associated APIs. Participate in maintaining and improving existing machine learning systems, addressing issues, and integrating new features.
• Research and Innovation: Stay abreast of the latest trends, techniques, and tools in machine learning and AI. Continuously explore new methodologies and technologies to enhance the efficiency and effectiveness of our machine learning solutions, including areas of operational machine learning, explainability, and robust AI.

What you need to have

Bachelor's Degree in Computer Science, Data Science, Statistics or related field and 5 years of related experience is required; additional experience may be considered in lieu of degree; an advanced degree may substitute for 2 years of experience.

• Substantial experience in machine learning, including proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch, or scikit-learn).
• Demonstrated expertise in various machine learning algorithms and models, including but not limited to decision trees, neural networks, clustering, and regression models. Code samples or online repositories may be requested.
• Proficiency in programming languages used in machine learning, such as Python or R. Experience with libraries for data manipulation and analysis, like pandas and NumPy, is beneficial.
• Experience with ML deployment frameworks like MLFlow
• Experience in developing, evaluating, and deploying machine learning models in production environments and monitoring deployed models for performance, drift, bias.
• Experience working with databases and SQL, as well as skills in data modeling, optimization, and query performance tuning.
• Solid understanding of RESTful APIs and experience designing and implementing APIs for machine learning model serving.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their associated services for deploying and managing machine learning applications.
• Strong problem-solving skills and the ability to analyze complex datasets, extract insights, and provide innovative machine learning solutions.
• Excellent teamwork and communication skills, with the ability to collaborate effectively with diverse teams and stakeholders.
• Meticulous attention to detail and commitment to producing high-quality models and deliverables.

What we'd like you to have

• Familiarity with natural language processing (NLP), computer vision, and deep learning.
• Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes).
• Familiarity with continuous integration and deployment (CI/CD) pipelines.
• Contributions to open-source machine learning projects or active participation in the machine learning community.
• Past LLM usage like hugging face / langchain 
• Familiarity with Agile/Scrum methodologies.

About BigBear.ai

BigBear.ai delivers AI-powered analytics and cyber engineering solutions to support mission-critical operations and decision-making in complex, real-world environments. BigBear.ai’s customers, which include the US Intelligence Community, Department of Defense, the US Federal Government, as well as customers in manufacturing, healthcare, commercial space, and other sectors, rely on BigBear.ai’s solutions to see and shape their world through reliable, predictive insights and goal-oriented advice. Headquartered in Columbia, Maryland, BigBear.ai is a global, public company traded on the NYSE under the symbol BBAI. For more information, please visit: http://bigbear.ai/ and follow BigBear.ai on Twitter: @BigBearai.