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Machine Learning Software Engineer Intern Jobs in Minnesota

Bespoke Labs

Machine Learning Engineer

Plymouth, MN · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

ITW North Star Imaging

Software Engineer

Rogers, MN

$68K - $84K/yr

We are seeking an early career Software Engineer to join our Engineering Innovation team. In this ... Experience with Machine Learning, tools like Claude/Cursor, PyTorch, TensorFlow * Self-motivated ...

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Machine Learning Software Engineer Intern information

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 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 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

Bespoke Labs

Minneapolis, MN • On-site

Full-time

Posted 21 days ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

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