Senior Machine Learning Operations Engineer

What You'll Do

• Design, develop, and implement end-to-end machine learning pipelines, from data ingestion and preprocessing to model training, evaluation, and deployment.
• Collaborate with the general software engineering team to integrate ML models into existing software systems and ensure scalability and maintainability.
• Work in conjunction with computer vision specialists to apply and optimize ML techniques for image and video analysis, object detection, tracking, and recognition in defense contexts.
• Research and evaluate new machine learning algorithms, tools, and technologies to enhance our capabilities and solve challenging problems.
• Perform rigorous model testing, validation, and performance tuning to ensure robustness and accuracy in real-world scenarios.
• Contribute to the development of best practices for ML engineering, including MLOps, version control, and reproducible research.
• Mentor junior engineers and contribute to a culture of continuous learning and knowledge sharing.
• Communicate technical concepts effectively to both technical and non-technical stakeholders.

What You'll Need

Education: Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.

Experience: 5+ years of experience in machine learning engineering, with a proven track record of deploying ML models in production environments.

Technical Skills:

• Strong proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Solid understanding of core machine learning concepts, including supervised, unsupervised, and reinforcement learning.
• Experience with various machine learning model architectures and their application (e.g., CNNs, RNNs, Transformers, decision trees, support vector machines).
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
• Experience with MLOps tools and practices.
• Experience deploying a variety of edge systems.
• Experience with TensorRT and other similar technologies.
• Deep knowledge of C++ and Python.

Domain Knowledge:

• Experience or strong interest in defense, aerospace, or related industries is highly desirable.
• Understanding of the unique challenges and considerations for deploying ML in defense applications (e.g., adversarial robustness, real-time constraints, data security).

Collaboration & Communication:

• Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
• Ability to translate complex technical concepts into clear and concise language.

Problem-Solving:

• Strong analytical and problem-solving skills, with a proactive and innovative approach.
• Ability to work independently and manage multiple priorities in a fast-paced environment.

Bonus Points

• Experience with specific computer vision tasks such as object detection, segmentation, or tracking.
• Familiarity with real-time ML systems and embedded systems.
• Contributions to open-source projects or publications in relevant fields.

What We Offer

• Competitive salary, equity, and benefits package.
• Opportunity to work on cutting-edge technology with a significant impact on national security.
• A collaborative work environment that values innovation.
• Professional development opportunities and career growth.