Senior Machine Learning Engineer

Anno.ai-posted 20 days ago
Full-time • Senior
Minneapolis, MN
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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.

  • 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
  • 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%
  • 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
  • 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
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