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Machine Learning Software Engineer Intern Jobs in Minnesota

Virtusa

Machine Learning Engineer

Minneapolis, MN · On-site

Required Qualification:- - 5+ years software engineering with 2+ years shipping ML models to ... 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 ... Required Qualification:- - 5 years software engineering with 2 years shipping ML models to ...

Autodesk

$106.80K - $138.70K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East ... Your skills span test strategy, automation, and a little MLOps, with a strong software engineering ...

Shipt

Staff Machine Learning Engineer

Minneapolis, MN · On-site +1

PhD/MS in Computer Science, Engineering, Mathematics or equivalent work experience * 5+ years of experience in machine learning and backend software engineering * Proficiency in at least one backend ...

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Machine Learning Software Engineer Intern information

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

To thrive as a Machine Learning Software Engineer Intern, you need a solid understanding of programming (especially Python), machine learning algorithms, and data structures, ideally supported by coursework or relevant projects. Familiarity with frameworks such as TensorFlow or PyTorch, experience using version control systems like Git, and knowledge of cloud platforms are highly valuable. Critical thinking, eagerness to learn, and effective communication help interns collaborate with teams and adapt to new challenges. These skills and qualities are crucial for developing robust ML solutions, integrating with production systems, and contributing meaningfully to real-world projects.

What types of projects and responsibilities can a Machine Learning Software Engineer Intern expect during their internship?

As a Machine Learning Software Engineer Intern, you can expect to work on projects that involve data preprocessing, model development, and evaluation under the guidance of experienced engineers and data scientists. Interns often contribute to building and optimizing machine learning pipelines, implementing algorithms, and supporting the deployment of models into production environments. Collaboration is key; you'll likely work closely with cross-functional teams, including product managers and software developers, to ensure your solutions align with business goals. The internship is a great opportunity to gain hands-on experience with industry-standard tools and frameworks while receiving mentorship and feedback to help advance your technical skills.

What does a Machine Learning Software Engineer Intern do?

A Machine Learning Software Engineer Intern assists in the development, testing, and deployment of machine learning models and algorithms. Their responsibilities typically include data preprocessing, model training, evaluation, and collaborating with senior engineers to integrate machine learning solutions into software products. Interns may also contribute to research, documentation, and code optimization, gaining hands-on experience with real-world machine learning projects. This role provides a valuable opportunity to apply academic knowledge in a professional setting and learn from experienced engineers.
What are the most commonly searched types of Machine Learning Software Engineer jobs in Minnesota? The most popular types of Machine Learning Software Engineer jobs in Minnesota are:
Machine Learning Software Engineer Intern jobs near you
Machine Learning Engineer

Machine Learning Engineer

Virtusa

Minneapolis, MN • On-site

Other

Posted 17 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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