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Machine Learning Engineer Jobs in Rosemount, MN (NOW HIRING)

AI Center of Excellence as a Machine Learning Engineer Consultant! In this exciting role, you?ll collaborate with talented experts to build innovative solutions that address our company?s evolving ...

We're looking for a Principal Machine Learning Engineer to build AI features for the family. Qualifications: * A confident craftsperson who possesses problem-solving tools and can discuss multiple ...

Remote Our client seeks a Senior AI/ML Engineer to design and deliver cloud-native machine learning solutions on AWS. The role includes LLM orchestration, RAG pipelines, vector database integration ...

Machine Learning Engineer Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve ...

Machine Learning Engineer Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve ...

AI Solutions Architect

Minneapolis, MN · On-site

$65.75 - $86.75/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

Lead AI/ML Engineer

Eden Prairie, MN

$104K - $137K/yr

Machine Learning Project Lead Drive end-to-end machine learning projects that have a high degree of ... AI Additional Skills: NLP Engineer, ML Engineer, ML Developer, Generative AI Developer, AI ...

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$131.7K

$197.8K

How much do machine learning engineer jobs pay per year?

As of Jun 11, 2026, the average yearly pay for machine learning engineer in Rosemount, MN is $131,652.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,800.00 and $158,500.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Rosemount, MN? The most popular types of Machine Learning Engineer jobs in Rosemount, MN are:
What are popular job titles related to Machine Learning Engineer jobs in Rosemount, MN? For Machine Learning Engineer jobs in Rosemount, MN, the most frequently searched job titles are:
What cities near Rosemount, MN are hiring for Machine Learning Engineer jobs? Cities near Rosemount, MN with the most Machine Learning Engineer job openings:
ML Engineer

ML Engineer

York Solutions, LLC

Saint Paul, MN • On-site, Remote

Other

Medical, Dental, Vision, Life, Retirement

Posted 12 days ago


Job description


AI Center of Excellence as a Machine Learning Engineer Consultant! In this exciting role, you?ll collaborate with talented experts to build innovative solutions that address our company?s evolving business challenges.
Primary Responsibilities:
Lead the design and development of ML pipelines for advanced AI algorithms and ML models to solve complex problems across diverse business domains.
Collaborate on development of ML architecture and implement robust, efficient, and scalable AI systems that integrate seamlessly with existing infrastructure and platforms.
Collaborate with research scientists, data scientists, and software engineers to translate research findings into practical, scalable AI solutions.
Evaluate and experiment with emerging AI technologies, frameworks, and methodologies to stay at the forefront of innovation. Provide technical guidance and mentorship to junior team members, fostering a culture of continuous learning and growth.
Collaborate with stakeholders to understand requirements, gather feedback, and iterate on AI solutions to ensure alignment with business objectives.
Deploy, test, and optimize ML models and data pipelines in production environments.
Perform model tuning, prompt tuning, and other ML optimization processes alongside other technical experts to maximize the mission impact of the AI product.
Participate in the delivery, evaluation, and maintenance of enterprise products, ensuring they meet high-quality standards.
Qualifications:
Advanced degree (Master's or Ph.D.) or equivalent industry experience in Computer Science, Machine Learning, or related fields.
5+ years of experience in a similar role in a production environment.
Experience working with large scale datasets and building ETL pipelines using Spark, Kubeflow, StreamSets, etc.
Hands-on experience with cloud computing platforms such as AWS.
Strong proficiency in Python and experience with NLP techniques, resources, and methodologies such as Scikit-learn, TensorFlow, PyTorch, HuggingFace, Comprehend, XGBoost, LangChain, etc.
Experience integrating machine learning models and data-driven algorithms into larger system architectures that involve pieces like Flask, ElasticSearch, PostgreSQL, IBM MQ, Apache Kafka, etc.
Experience with iterative development processes, thriving in dynamic and agile environments.
Ability to own ML delivery tasks end-to-end with little to no direct support. Hands-on experience in deploying machine learning models into production environments.
Strong understanding of software design patterns, principles, architecture, and operations.
Strong communication skills and the ability to collaborate effectively with business partners, vendors, end users, and cross-functional teams
Benefits:
York Solutions Offers a generous benefits package for eligible full-time employees:

  • BCBS Medical with 3 Plans to choose from (PPO and High deductible PPO plans with Health Savings Program)
  • Delta Dental plan with 2 free cleanings and insurance discounts
  • Eye Med Vision with annual check-ups and discounts on lens
  • Life and Accidental Death Insurance paid by company
  • John Hancock 401(k) Retirement Plan with discretionary company match
  • Voluntary Insurance programs such as: Hospital Indemnity, Identity Protection, Legal Insurance, Long Term Care, and Pet Insurance.
  • Flexible work environment with some remote working opportunities
  • Strong fun and teamwork environment
  • Learning, development, and career growth