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Machine Learning Scientist Intern Jobs in Prior Lake, 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 ... Required : • Bachelor's degree in Computer Science, Electrical Engineering, Data Science, or a ...

On-Demand Group

Sr. Data Scientist

Minneapolis, MN · On-site

Evaluate and recommend appropriate machine learning algorithms and modeling techniques * Monitor ... Mentor junior and mid-level Data Scientists through technical guidance, code reviews, and ...

Jobtailor

Senior Data Scientist

Minneapolis, MN · On-site

$120 - $180/hr

Expertise in data science, machine learning, data mining, operations research, and statistical modeling techniques, specifically for high-volume and complex datasets. * Knowledge of best coding ...

Strategic Education

Data Scientist II

Minneapolis, MN · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Data Scientist II leverages machine learning and Generative AI (LLMs) to deliver scalable, data-driven solutions that improve business performance and decision-making. This role builds and ...

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All JobsMachine Learning Scientist Intern JobsMachine Learning Scientist Intern Jobs in Prior Lake, MN

Machine Learning Scientist Intern information

See Prior Lake, MN salary details

$26.2K

$43.7K

$90.3K

How much do machine learning scientist intern jobs pay per year?

As of Aug 16, 2026, the average yearly pay for machine learning scientist intern in Prior Lake, MN is $43,702.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,400.00 and $47,200.00 per year, depending on experience, location, and employer.

What kinds of projects and collaborations can a machine learning scientist intern expect during their internship?

As a Machine Learning Scientist Intern, you can expect to work on real-world data-driven projects, often involving tasks like data preprocessing, developing and testing machine learning models, and analyzing model performance. Interns typically collaborate with experienced data scientists, engineers, and sometimes product teams, participating in regular meetings and code reviews. This role offers hands-on experience with large datasets and modern ML frameworks, along with mentorship to help you grow your technical and research skills. Working cross-functionally is common, so strong communication and teamwork are valuable assets.

What does a machine learning scientist intern do?

A Machine Learning Scientist Intern typically assists in designing, developing, and testing machine learning models to solve real-world problems. They collaborate with experienced scientists and engineers to analyze data, select appropriate algorithms, and evaluate model performance. Interns often contribute to research projects, data preprocessing, and implementation of prototypes. This role provides valuable hands-on experience in applying machine learning techniques to practical challenges and often involves learning and using tools such as Python, TensorFlow, or PyTorch.

What are the key skills and qualifications needed to thrive as a machine learning scientist intern, and why are they important?

To thrive as a Machine Learning Scientist Intern, you generally need a solid foundation in mathematics, statistics, and programming (especially Python), often supported by coursework or research experience in machine learning. Familiarity with tools and frameworks like TensorFlow, PyTorch, scikit-learn, and version control systems is typically expected. Strong problem-solving skills, curiosity, and effective communication help interns stand out when collaborating and presenting results. These skills and qualities are vital for effectively developing models, interpreting data, and contributing to innovative projects in a team environment.
Machine Learning Scientist Intern jobs near you

Senior Machine Learning Engineer

Onsights

Minneapolis, MN • On-site

$109K - $149K/yr

Full-time

Re-posted 11 hours 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:
Bringing online retail metrics, insights, and visibility you care about into your brick and mortar locations. 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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