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Senior Machine Learning Engineer
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Onsights .
What We Do at Anno.ai Anno.ai is a mission-focused defense technology startup dedicated to accelerating the safe and effective development of next-generation autonomous systems. We specialize in building and operating advanced test ranges for low Technology Readiness Level (TRL) single- or dual‑use autonomous platforms, providing a critical bridge between early-stage innovation and real-world mission requirements.
Our ranges replicate complex, contested, and dynamic environments—giving innovators, researchers, and defense partners the ability to validate, stress‑test, and mature their systems with speed and rigor. By combining deep technical expertise with a strong national security ethos, Anno.ai ensures that emerging autonomous technologies are tested not only for performance, but for resilience, adaptability, and operational relevance.
Anno.ai is a growing company with a team drawn from diverse professional backgrounds, bringing together expertise in defense, technology, engineering, and operations. We intentionally build our teams on the foundation of trust. Our values—including the trust rule, ownership, bias for action, never stop learning, and sustainable excellence—guide how we work internally and how we partner with customers and stakeholders.
At Anno.ai, we believe that mission success depends on empowering innovation at the edge. We exist to help our partners move faster, fail smarter, and ultimately deliver autonomous capabilities that safeguard both national security and the future of global stability.
Position Overview As a Senior Machine Learning Engineer at Anno.ai, you will design, develop, test, document, deploy, and maintain production machine learning and statistical software to automate processes and streamline our customer's mission operations. MLEs work directly with product, user-facing, hardware, and platform teams to deliver the highest quality products. Annomals are practical, mission‑driven, and fun. We value good management, your career growth, and ethical, responsible practices.
For this opportunity we are looking for MLEs who have a fairly uniform distribution of talent across the range of machine learning tasks and skills. You are an experienced MLE, part solid software engineer, part modeling expert.
The ideal candidate for this role would reside in Minnesota.
Candidates need to be able to obtain and maintain U.S. Government security clearance (U.S. citizenship required). The company would pay for clearance costs. They also need to be able to travel up to 20% of the time.
What You Will Do
Operationalize machine learning models by building robust, scalable pipelines for training, evaluation, deployment, and lifecycle management across cloud, on‑prem, and edge compute environments
Work closely with autonomy researchers, software engineers, systems teams, and field operators to translate mission requirements into deployable ML capabilities
Implement automated CI/CD workflows tailored to ML systems, ensuring repeatable experiments, reliable packaging, and continuous delivery of both models and data pipelines
Manage ML runtime infrastructure using containerization and orchestration frameworks (e.g., Docker, Kubernetes) and model serving platforms (e.g., Seldon, KServe, BentoML)
Develop monitoring systems to track model health, performance, data drift, system utilization, and mission relevance using tools such as Prometheus, Grafana, and ELK/EFK stacks
Ensure ML deployments meet defense, customer, and platform security requirements, with emphasis on data integrity, traceability, and operational reliability
Evaluate and integrate emerging MLOps, distributed training, and edge inference technologies to enhance reproducibility, scalability, and deployment speed of ML systems
Required Qualifications
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)
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
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 Qualifications
Prior experience supporting U.S. Department of War programs, cUAS systems, or mission‑critical autonomous platforms
Experience working with diverse or atypical data sources (e.g., audio/acoustics, RF signals, EO/IR imagery)
Experience deploying and optimizing ML inference on edge or resource‑limited compute systems
Experience with Explainable/Auditable AI/ML tools and interpretable model design
Total Rewards Package for Our US Employees
Competitive salary
Equity
Comprehensive benefits package
401(k) 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
Quick Note on Role Fit If you think you have what it takes to fulfill this opportunity, but don’t necessarily check every box, please still connect with us at talent@anno.ai. Feel free to send a cover letter so we can get to know you better!
Seniority level
Mid‑Senior level
Employment type
Full‑time
Job function
Engineering and Information Technology
Software Development
#J-18808-Ljbffr
Senior Machine Learning Engineer
role at
Onsights .
What We Do at Anno.ai Anno.ai is a mission-focused defense technology startup dedicated to accelerating the safe and effective development of next-generation autonomous systems. We specialize in building and operating advanced test ranges for low Technology Readiness Level (TRL) single- or dual‑use autonomous platforms, providing a critical bridge between early-stage innovation and real-world mission requirements.
Our ranges replicate complex, contested, and dynamic environments—giving innovators, researchers, and defense partners the ability to validate, stress‑test, and mature their systems with speed and rigor. By combining deep technical expertise with a strong national security ethos, Anno.ai ensures that emerging autonomous technologies are tested not only for performance, but for resilience, adaptability, and operational relevance.
Anno.ai is a growing company with a team drawn from diverse professional backgrounds, bringing together expertise in defense, technology, engineering, and operations. We intentionally build our teams on the foundation of trust. Our values—including the trust rule, ownership, bias for action, never stop learning, and sustainable excellence—guide how we work internally and how we partner with customers and stakeholders.
At Anno.ai, we believe that mission success depends on empowering innovation at the edge. We exist to help our partners move faster, fail smarter, and ultimately deliver autonomous capabilities that safeguard both national security and the future of global stability.
Position Overview As a Senior Machine Learning Engineer at Anno.ai, you will design, develop, test, document, deploy, and maintain production machine learning and statistical software to automate processes and streamline our customer's mission operations. MLEs work directly with product, user-facing, hardware, and platform teams to deliver the highest quality products. Annomals are practical, mission‑driven, and fun. We value good management, your career growth, and ethical, responsible practices.
For this opportunity we are looking for MLEs who have a fairly uniform distribution of talent across the range of machine learning tasks and skills. You are an experienced MLE, part solid software engineer, part modeling expert.
The ideal candidate for this role would reside in Minnesota.
Candidates need to be able to obtain and maintain U.S. Government security clearance (U.S. citizenship required). The company would pay for clearance costs. They also need to be able to travel up to 20% of the time.
What You Will Do
Operationalize machine learning models by building robust, scalable pipelines for training, evaluation, deployment, and lifecycle management across cloud, on‑prem, and edge compute environments
Work closely with autonomy researchers, software engineers, systems teams, and field operators to translate mission requirements into deployable ML capabilities
Implement automated CI/CD workflows tailored to ML systems, ensuring repeatable experiments, reliable packaging, and continuous delivery of both models and data pipelines
Manage ML runtime infrastructure using containerization and orchestration frameworks (e.g., Docker, Kubernetes) and model serving platforms (e.g., Seldon, KServe, BentoML)
Develop monitoring systems to track model health, performance, data drift, system utilization, and mission relevance using tools such as Prometheus, Grafana, and ELK/EFK stacks
Ensure ML deployments meet defense, customer, and platform security requirements, with emphasis on data integrity, traceability, and operational reliability
Evaluate and integrate emerging MLOps, distributed training, and edge inference technologies to enhance reproducibility, scalability, and deployment speed of ML systems
Required Qualifications
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)
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
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 Qualifications
Prior experience supporting U.S. Department of War programs, cUAS systems, or mission‑critical autonomous platforms
Experience working with diverse or atypical data sources (e.g., audio/acoustics, RF signals, EO/IR imagery)
Experience deploying and optimizing ML inference on edge or resource‑limited compute systems
Experience with Explainable/Auditable AI/ML tools and interpretable model design
Total Rewards Package for Our US Employees
Competitive salary
Equity
Comprehensive benefits package
401(k) 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
Quick Note on Role Fit If you think you have what it takes to fulfill this opportunity, but don’t necessarily check every box, please still connect with us at talent@anno.ai. Feel free to send a cover letter so we can get to know you better!
Seniority level
Mid‑Senior level
Employment type
Full‑time
Job function
Engineering and Information Technology
Software Development
#J-18808-Ljbffr