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Deep Learning Jobs in Minnesota (NOW HIRING)

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 ...

Bespoke Labs

Machine Learning Engineer

Rochester, 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 ...

Bespoke Labs

Machine Learning Engineer

Duluth, 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 ...

AeroVironment

Machine Learning Engineer III

Minneapolis, MN

$129K - $197K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

Proficiency with a deep learning framework such as TensorFlow or Keras * Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas * Expertise in visualizing ...

Onsights

Senior Machine Learning Engineer

Minneapolis, MN · On-site

$109K - $149K/yr

... 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 ...

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Deep Learning information

See Minnesota salary details

$10.8K

$82.2K

$137.1K

How much do deep learning jobs pay per year?

As of Aug 16, 2026, the average yearly pay for deep learning in Minnesota is $82,158.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,500.00 and $136,100.00 per year, depending on experience, location, and employer.

What is a deep learning job?

A Deep Learning job involves designing, developing, and optimizing neural networks to solve complex problems such as image recognition, natural language processing, and autonomous systems. Professionals in this field work with large datasets, neural network architectures, and frameworks like TensorFlow or PyTorch. They collaborate with data scientists, engineers, and researchers to improve model accuracy and efficiency. Deep Learning roles typically require strong programming skills in Python, knowledge of machine learning algorithms, and experience with GPU acceleration.

What are the typical daily responsibilities of a deep learning professional?

As a Deep Learning professional, your day-to-day tasks often include designing and training neural network models, preprocessing and analyzing large datasets, and evaluating model performance using various metrics. You may also participate in research activities, document your results, and collaborate with data scientists, engineers, or product teams to deploy machine learning solutions. Regular meetings for project updates, code reviews, and brainstorming sessions are common, as is staying updated on advances in the field. This dynamic environment offers both individual and team-based work, providing continuous learning and the opportunity to solve complex, real-world problems.

What are the key skills and qualifications needed to thrive in a deep learning position?

To thrive in Deep Learning, you need a solid understanding of machine learning theory, neural networks, mathematics (especially linear algebra and probability), and programming skills, typically backed by a degree in computer science, mathematics, or a related field. Familiarity with frameworks such as TensorFlow or PyTorch, experience with data preprocessing, and optionally industry-recognized certifications are advantageous. Strong analytical thinking, problem-solving skills, and the ability to communicate findings clearly are crucial soft skills. These abilities enable the design, implementation, and optimization of effective deep learning solutions in real-world applications.

What are the most commonly searched types of Deep Learning jobs in Minnesota?

The most popular types of Deep Learning jobs in Minnesota are:

What are popular job titles related to Deep Learning jobs in Minnesota?

For Deep Learning jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Deep Learning jobs in Minnesota look for?

The top searched job categories for Deep Learning jobs in Minnesota are:

Deep Learning jobs near you
Infographic showing various Deep Learning job openings in Minnesota as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $82,158 per year, or $39.5 per hour.

Machine Learning Engineer

Bespoke Labs

Plymouth, MN • On-site

Full-time

Re-posted 12 hours 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

Apply