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Freelance Computer Vision Deep Learning Engineer Jobs in Philadelphia, PA

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 ...

Guthrie AI is hiring a Founding AI / ML Engineer with deep expertise in Computer Vision to lead model development for the platform. * Construction diagrams and floor plans are not included in the ...

Senior Machine Learning Engineer

Malvern, PA

$120K - $158K/yr

We are assisting our client in hiring for a Senior Machine Learning Engineer. Our client is an ... Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a ...

CCB Risk Program Associate

Wilmington, DE

$57K - $57K/yr

The CCB Risk Modeling team is seeking talented professionals with expertise in computer vision ... Apply state-of-the-art machine learning methodologies - including deep learning architecture ...

Showing results 41-60

Freelance Computer Vision Deep Learning Engineer information

See Philadelphia, PA salary details

$15

$48

$133

How much do freelance computer vision deep learning engineer jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for freelance computer vision deep learning engineer in Philadelphia, PA is $48.14, according to ZipRecruiter salary data. Most workers in this role earn between $24.52 and $62.36 per hour, depending on experience, location, and employer.
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Machine Learning Engineer

Bespoke Labs

Philadelphia, PA • On-site

Full-time

Re-posted 20 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