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Apprentice Machine Learning Testing Jobs in Minnesota

Virtusa

Machine Learning Engineer

Minneapolis, MN · On-site

... testing. - Implement scalable model serving (online/offline), batching, and latency/throughput ... Role Summary:- Builds, trains and tunes machine learning models. Translates data science ...

Virtusa

Machine Learning Engineer

Minneapolis, MN · On-site

Role Summary:- Builds, trains and tunes machine learning models. Translates data science ... testing. - Implement scalable model serving (online/offline), batching, and latency/throughput ...

Virtusa

Machine Learning Engineer

Minneapolis, MN · On-site

Role Summary:- Builds, trains and tunes machine learning models. Translates data science ... testing. - Implement scalable model serving (online/offline), batching, and latency/throughput ...

AeroVironment

Machine Learning Engineer III

Minneapolis, MN · On-site

$129.50K - $183.75K/yr

... testing. Citizenship * To qualify for this role US citizenship is required. Position Responsibilities * Support development of computer vision and machine learning algorithms capable of detection ...

AeroVironment

Machine Learning Engineer II

Minneapolis, MN · On-site

$102K - $144.38K/yr

... testing. Citizenship To qualify for this role you must be a US citizen Position Responsibilities: * Support development of computer vision and machine learning (ML) algorithms capable of detection ...

Autodesk

$106.80K - $138.70K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East ... API Testing * Automate ML QA workflows using Python and CI/CD (e.g., GitHub Actions, Jenkins)

Clow

Machinist Apprentice

Merrifield, MN · On-site

$20.25/hr

Clow is looking for motivated individuals to join our manufacturing team as Machinist Apprentices ... This position is a great fit for someone who enjoys learning, working with machinery, and building ...

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Apprentice Machine Learning Testing information

What are the key skills and qualifications needed to thrive as an Apprentice Machine Learning Testing, and why are they important?

To thrive as an Apprentice in Machine Learning Testing, a foundational understanding of statistics, programming (especially Python), and basic machine learning concepts is essential, often supported by a degree or coursework in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, Jupyter Notebooks, and version control systems is typically required. Strong analytical thinking, attention to detail, and effective communication skills help apprentices collaborate and identify testing issues efficiently. These skills ensure accurate model validation, effective troubleshooting, and contribute to the robust deployment of machine learning solutions.

What kinds of projects or tasks can I expect to work on as an Apprentice Machine Learning Testing?

As an Apprentice Machine Learning Testing, you’ll typically assist in evaluating machine learning models by designing and running tests, analyzing model outputs, and helping identify issues like bias or overfitting. You may work closely with data scientists and software engineers to validate model performance and ensure results align with project objectives. Your daily tasks might include preparing test datasets, executing automated testing scripts, and documenting findings to help improve model reliability. This role often serves as a valuable introduction to practical machine learning workflows and quality assurance processes in technical teams.

What does an Apprentice Machine Learning Testing do?

An Apprentice Machine Learning Testing professional assists in evaluating and validating machine learning models to ensure they perform as expected. They typically work under the guidance of experienced data scientists or engineers, running tests, analyzing results, and helping to identify issues such as bias or inaccuracies in algorithms. Their responsibilities may also include developing test cases, writing reports, and learning about data preprocessing and evaluation metrics. This role is ideal for those who are new to the field and want to build foundational skills in machine learning quality assurance.

What is the difference between Apprentice Machine Learning Testing vs Machine Learning Engineer?

AspectApprentice Machine Learning TestingMachine Learning Engineer
Required CredentialsBasic understanding of ML concepts, often pursuing relevant certifications or degreesAdvanced degrees (BSc, MSc, PhD) in CS or related fields, with extensive experience
Work EnvironmentEntry-level, supervised testing environments, often in training programsFull-time, independent development and deployment of ML models in production
Employer & Industry UsageInternships, training programs, entry-level roles in tech companiesEstablished tech firms, startups, research institutions

Apprentice Machine Learning Testing roles focus on learning and assisting with testing ML models under supervision, while Machine Learning Engineers design, build, and deploy ML systems independently. The apprentice position is ideal for gaining foundational skills, whereas the engineer role requires advanced expertise and experience.

What are popular job titles related to Apprentice Machine Learning Testing jobs in Minnesota? For Apprentice Machine Learning Testing jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Apprentice Machine Learning Testing jobs in Minnesota look for? The top searched job categories for Apprentice Machine Learning Testing jobs in Minnesota are:
What cities in Minnesota are hiring for Apprentice Machine Learning Testing jobs? Cities in Minnesota with the most Apprentice Machine Learning Testing job openings:
Apprentice Machine Learning Testing jobs near you
Machine Learning Engineer

Machine Learning Engineer

Virtusa

Minneapolis, MN • On-site

Other

Posted 15 days ago

Job description

Role Summary:-


Builds, trains and tunes machine learning models. Translates data science experiments into scalable, production-ready ML solutions.


Ker Responsibilities

- Translate data science prototypes into production-grade ML services and pipelines.

- Build training and inference code with reproducibility, versioning, and automated testing.

- Implement scalable model serving (online/offline), batching, and latency/throughput optimization.

- Integrate model lifecycle tooling (tracking, registry, deployment automation, monitoring).

- Collaborate with Data Engineering on feature pipelines and data contracts.

- Own production health: drift detection, performance regression, rollback strategies, and incident response.


Required Qualification:-

- 5+ years software engineering with 2+ years shipping ML models to production.

- Strong Python skills and experience with ML frameworks (TensorFlow/PyTorch).

- Experience with containers and orchestration (Docker/Kubernetes) and API development.

- Understanding of ML system design (data leakage, training-serving skew, drift).

- CI/CD and DevOps practices applied to ML workloads (MLOps).


Nice to have:-

- Experience with feature stores, model registries, and model monitoring stacks.

- GPU optimization and distributed training experience.

- Experience with responsible AI toolkits and compliance requirements.


 

Role Summary:-


Builds, trains and tunes machine learning models. Translates data science experiments into scalable, production-ready ML solutions.


Ker Responsibilities

- Translate data science prototypes into production-grade ML services and pipelines.

- Build training and inference code with reproducibility, versioning, and automated testing.

- Implement scalable model serving (online/offline), batching, and latency/throughput optimization.

- Integrate model lifecycle tooling (tracking, registry, deployment automation, monitoring).

- Collaborate with Data Engineering on feature pipelines and data contracts.

- Own production health: drift detection, performance regression, rollback strategies, and incident response.


Required Qualification:-

- 5+ years software engineering with 2+ years shipping ML models to production.

- Strong Python skills and experience with ML frameworks (TensorFlow/PyTorch).

- Experience with containers and orchestration (Docker/Kubernetes) and API development.

- Understanding of ML system design (data leakage, training-serving skew, drift).

- CI/CD and DevOps practices applied to ML workloads (MLOps).


Nice to have:-

- Experience with feature stores, model registries, and model monitoring stacks.

- GPU optimization and distributed training experience.

- Experience with responsible AI toolkits and compliance requirements.


 

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About Virtusa

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We are builders, makers, and doers with the technical skills and domain expertise to transform your business at scale and speed without disruption. Our unique Engineering First approach blends deep industry expertise and empowered, agile teams, to create holistic solutions that seamlessly move the business forward. We help clients engage with new technology paradigms to creatively build solutions that drive them to the forefront of their industries.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Westborough, MA, US

Year founded

1996

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