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Live In Medical Image Deep Learning Jobs in Tennessee

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 ...

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 ...

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 ...

Senior Machine Learning Engineer

Nashville, TN · On-site

$100K - $138K/yr

We encourage you to apply and take the first step in joining our dynamic and impactful company ... Experience with deep learning architectures (CNNs, RNNs, Transformers) * Experience applying ML to ...

We encourage you to apply and take the first step in joining our dynamic and impactful company ... Experience with deep learning architectures (CNNs, RNNs, Transformers) * Experience applying ML to ...

Showing results 41-60

Live In Medical Image Deep Learning information

What is the difference between Live In Medical Image Deep Learning vs Medical Imaging Specialist?

AspectLive In Medical Image Deep LearningMedical Imaging Specialist
CredentialsTypically requires a degree in computer science, AI, or related fields; certifications in deep learning or medical imaging are commonRequires degrees in radiology, medical imaging technology, or related healthcare fields; certifications in imaging modalities are often needed
Work EnvironmentPrimarily research labs, AI development teams, or healthcare tech companies; involves programming and data analysisHospitals, clinics, diagnostic centers; involves operating imaging equipment and patient interaction
Industry UsageUsed in developing AI algorithms for medical image analysis, diagnostics, and researchUsed in performing and interpreting medical imaging procedures for patient diagnosis

Live In Medical Image Deep Learning focuses on developing AI models for analyzing medical images, requiring programming and data science skills. In contrast, Medical Imaging Specialists perform imaging procedures and interpret results in clinical settings. Both roles are essential in healthcare but differ in their focus and daily tasks.

What are the most commonly searched types of Medical Image Deep Learning jobs in Tennessee? The most popular types of Medical Image Deep Learning jobs in Tennessee are:
What cities in Tennessee are hiring for Live In Medical Image Deep Learning jobs? Cities in Tennessee with the most Live In Medical Image Deep Learning job openings:

Machine Learning Engineer

Bespoke Labs

Jackson, TN • On-site

Full-time

Re-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