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Senior Deep Learning Engineer Jobs in Minneapolis, MN

Onsights

Senior Machine Learning Engineer

Minneapolis, MN · On-site

$109K - $149K/yr

As a Senior Machine Learning Engineer, you will design, develop, test, document, deploy, and ... one deep learning framework (e.g., PyTorch, TensorFlow) • Hands-on experience with MLOps ...

AeroVironment

Machine Learning Engineer III

Minneapolis, MN · On-site

$129K - $197K/yr

These development efforts will generally be small focused design teams which will require a senior ... Proficiency with a deep learning framework such as TensorFlow or Keras * Proficiency with Python ...

Kitware

Machine Learning Engineer

Minneapolis, MN · On-site

$85K - $125K/yr

We have developed a deep understanding in extracting useful, actionable information from multiple ... Engineering, or related field * Proficiency in Python * Experience with deep learning libraries ...

Kitware

Machine Learning Engineer

Minneapolis, MN · On-site

$85K - $125K/yr

We have developed a deep understanding in extracting useful, actionable information from multiple ... Engineering, or related field * Proficiency in Python * Experience with deep learning libraries ...

Kitware

Machine Learning Engineer

Minneapolis, MN

We have developed a deep understanding in extracting useful, actionable information from multiple ... Engineering, or related field * Proficiency in Python * Experience with deep learning libraries ...

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All JobsDeep Learning Engineer JobsSenior Deep Learning Engineer JobsSenior Deep Learning Engineer Jobs in Minneapolis, MN

Senior Deep Learning Engineer information

See Minneapolis, MN salary details

$62.1K

$132.1K

$191.5K

How much do senior deep learning engineer jobs pay per year?

As of Aug 29, 2026, the average yearly pay for senior deep learning engineer in Minneapolis, MN is $132,100.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,100.00 and $149,800.00 per year, depending on experience, location, and employer.

What is the difference between Senior Deep Learning Engineer vs Data Scientist?

AspectSenior Deep Learning EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with deep learning frameworksBachelor's or Master's in CS, Statistics, or related; proficiency in data analysis tools
Work EnvironmentDevelops and deploys deep learning models, often in AI teamsAnalyzes data, builds models, and provides insights across departments
Industry UsageTech, AI, and research companiesFinance, healthcare, marketing, and tech sectors

While both roles require strong analytical skills and programming knowledge, Senior Deep Learning Engineers focus on designing and implementing deep learning models, whereas Data Scientists analyze data to generate insights. The roles often collaborate but serve different primary functions within organizations.

Senior Machine Learning Engineer

Minneapolis, MN • On-site

Onsights
See more jobs at Onsightsexternal

$109K - $149K/yr

Full-time

Re-posted 14 days ago

Job description

Job Summary:
Anno.ai is a mission-focused defense technology startup dedicated to accelerating the safe and effective development of next-generation autonomous systems. As a Senior Machine Learning Engineer, you will design, develop, test, document, deploy, and maintain production machine learning and statistical modeled software to automate processes and streamline customer mission operations.
Responsibilities:
• Operationalize machine learning models by building and maintaining 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 up to date models and associated data pipelines
• Manage ML runtime infrastructure using containerization and orchestration frameworks (e.g., Docker, Kubernetes) and incorporating 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, extensibility, scalability, and deployment speed of ML systems
Qualifications:
Required:
• 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, 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 with deploying models and associated runtimes to Edged Devices
• Experience optimizing models for memory and CPU constrained systems (e.g., embedded systems, microcontrollers)
• 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
• Experience with AI Software Development Tools (e.g., GitHub CoPilot, Claude)
Company:
Online analytics for the physical world. Built on the tech you already own. Stop buying tools and start driving measurable progress. Founded in 2019, the company is headquartered in Minnetonka, USA, with a team of 11-50 employees. The company is currently Early Stage.

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