Senior Machine Learning Engineer

Job not on LinkedIn

🔥 14 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 15%

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Anno.Ai

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2018

🚀 Aerospace

🎖️ Defense

🏭 Manufacturing

Aerospace • Defense • Manufacturing

Anno. Ai is a company that provides dedicated test ranges, infrastructure, and technical services to accelerate Technical Readiness Level (TRL) and Manufacturing Readiness Level (MRL) for autonomous and unmanned vehicle platforms. Their offerings include the Arena and Lake Superior Test Range (LSTR) with surface, lakebed, and shore-based sensors, recovery resources, laboratories, warehousing, additive manufacturing and assembly facilities, and testing for UAS, cUAS, UGV, UUV, and USV platforms. They also provide sensor-based data labeling software and adversarial autonomous red cell services, serving both commercial and defense customers and emphasizing realistic, geographically diverse, and secure testing environments.

📋 Description

• Design, develop, test, document, deploy, and maintain production machine learning and statistical modeled software • Automate processes and streamline customers’ mission operations • Build and maintain robust, scalable pipelines for training, evaluation, deployment, and lifecycle management across cloud, on-premises, and edge compute environments • Work with autonomy researchers, software engineers, systems teams, and field operators to translate mission requirements into deployable ML capabilities • Implement automated CI/CD workflows for ML systems, including repeatable experiments, reliable packaging, and continuous delivery of models and data pipelines • Manage ML runtime infrastructure using Docker, Kubernetes, and model-serving platforms such as Seldon, KServe, and BentoML • Develop monitoring systems for model health, performance, data drift, system utilization, and mission relevance using Prometheus, Grafana, and ELK/EFK stacks • Ensure ML deployments meet defense, customer, and platform security requirements, emphasizing data integrity, traceability, and operational reliability • Evaluate and integrate emerging MLOps, distributed training, and edge inference technologies

🎯 Requirements

• Bachelor’s degree in Computer Science, Electrical Engineering, Data Science, or a related technical field (Master’s preferred) • 5+ years of professional experience in software engineering, machine learning engineering, MLOps, or related roles • Experience operationalizing ML systems at production scale, including model training, versioning, packaging, deployment, and monitoring • Strong proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow) • Hands-on experience with MLOps frameworks and workflow tooling (e.g., MLflow, Kubeflow, Airflow, DVC, BentoML) • Experience deploying containerized ML services using Docker and orchestrating workloads using Kubernetes, including air-gapped or constrained deployments • Understanding of CI/CD workflows and DevOps practices applied to ML systems, e.g., Git, code review, and metrics evaluation • Familiarity with monitoring, observability, and logging platforms, e.g., Prometheus, Grafana, ELK/EFK • Ability to obtain and maintain U.S. Government security clearance; U.S. citizenship required • Ability to travel up to 20% • Preferred: experience deploying models and runtimes to edge devices; optimizing models for memory- and CPU-constrained systems; supporting U.S. Department of War programs, cUAS systems, or mission-critical autonomous platforms; working with diverse data sources such as audio/acoustics, RF signals, and EO/IR imagery; deploying and optimizing ML inference on edge or resource-limited systems; Explainable/Auditable AI/ML tools and interpretable model design; AI software development tools such as GitHub Copilot and Claude

🏖️ Benefits

• Equity • Comprehensive benefits package • 401k with a 5% company match • Paid holidays and generous paid time off offering • Paid leave programs • Patent bonus program • Employee referral bonus program • Learning and development program • Opportunity to work with a team of highly skilled, creative and motivated team members

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