Senior Machine Learning Engineer
Company: Anno.ai
Location: Minneapolis
Posted on: February 13, 2026
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Job Description:
Job Description Job Description 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 are designed to 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, not only guide how we work internally,
but also 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 (e.g., Nvidia Jetson) Experience with Explainable/Auditable
AI/ML tools and interpretable model design Total Rewards Package
for Our US Employees Competitive salary 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 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!
Keywords: Anno.ai, Woodbury , Senior Machine Learning Engineer, IT / Software / Systems , Minneapolis, Minnesota