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Contractual Computer Vision Deep Learning Engineer Jobs in Iowa

Bespoke Labs

Machine Learning Engineer

Waterloo, IA · 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

Sioux City, IA · 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

Davenport, IA · 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

Clinton, IA · 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 ...

Tractor Zoom

Be Seen First

Senior Data Scientist

Des Moines, IA · On-site

$120K - $145K/yr

You will regularly work with our customers, designers, and engineers to build products used by ... Expertise in at least one subject area: computer vision, time series forecasting, deep learning ...

Kellton

Imaging Data Scientist

Johnston, IA · On-site

$75/hr

Design & deliver deep learning-based CV models for microscopy and macroscopic assays (detection ... in computer vision with Python (PyTorch/TensorFlow), including detection/segmentation ...

Workiva, Inc.

Staff Machine Learning Engineer

Ames, IA · On-site +1

As a pivotal member of our Machine Learning (ML) team, you'll spearhead the architecture and ... Bachelor's degree in Computer Science, Engineering or equivalent combination of education and ...

Varsity Tutors

Machine Learning Tutor

Ames, IA · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Varsity Tutors

Machine Learning Tutor

Iowa City, IA · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

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Machine Learning Engineer

Bespoke Labs

Cedar Rapids, IA • On-site

Full-time

Posted 7 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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