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Machine Learning Engineer Starting Jobs in Memphis, TN

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 ...

Machine Learning Tutor

Memphis, TN · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Python Developer (Entry Level)

Memphis, TN · On-site

$44.75 - $61.75/hr

We are matchmakers; we provide clients with candidates who can perform from day one of starting ... scientists, machine learning engineers for full-time positions with clients. Who should apply?

... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ... Projects are paid hourly starting at $50-100+/hr, with bonus rates available on some projects ...

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Showing results 1-20

Machine Learning Engineer Starting information

See Memphis, TN salary details

$28.1K

$114.9K

$172.7K

How much do machine learning engineer starting jobs pay per year?

As of Jun 28, 2026, the average yearly pay for machine learning engineer starting in Memphis, TN is $114,933.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,600.00 and $138,300.00 per year, depending on experience, location, and employer.
What cities near Memphis, TN are hiring for Machine Learning Engineer Starting jobs? Cities near Memphis, TN with the most Machine Learning Engineer Starting job openings:

Machine Learning Engineer

Bespoke Labs

Memphis, TN • On-site

Full-time

Posted 11 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