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Python Ai Developer Jobs in Clinton, MS (NOW HIRING)

Bespoke Labs

Machine Learning Engineer

Jackson, MS · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops ...

Cisco

Software Engineer, Backend

Jackson, MS · On-site

$152K - $219K/yr

Programming experience in Rust, Scala, Python. * Experience with observability tooling such ... the AI era - and beyond. We've been innovating fearlessly for 40 years to create solutions that ...

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How much do python ai developer jobs pay per hour?

As of Jul 5, 2026, the average hourly pay for python ai developer in Clinton, MS is $50.78, according to ZipRecruiter salary data. Most workers in this role earn between $41.83 and $57.69 per hour, depending on experience, location, and employer.

How does a Python AI Developer typically collaborate with data scientists and other team members during an AI project?

Python AI Developers often work closely with data scientists, machine learning engineers, and product managers throughout the lifecycle of an AI project. They are responsible for implementing algorithms and models designed by data scientists, optimizing code for efficiency, and integrating AI solutions into production environments. Regular communication and code reviews ensure alignment on objectives and technical standards, while agile practices like daily stand-ups facilitate cross-functional collaboration. Being open to feedback and adaptable to changing project requirements is key to success in this role.

What are the key skills and qualifications needed to thrive as a Python AI Developer, and why are they important?

To thrive as a Python AI Developer, you need strong programming skills in Python, a solid understanding of machine learning concepts, and a background in mathematics or computer science. Familiarity with frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, and experience with data processing tools are typically required. Analytical thinking, problem-solving abilities, and effective collaboration are crucial soft skills for this role. These competencies enable developers to design, implement, and optimize AI solutions that address complex real-world challenges efficiently.

What does a Python AI Developer do?

A Python AI Developer designs, builds, and implements artificial intelligence applications using the Python programming language. Their work often involves developing machine learning models, processing large datasets, and integrating AI solutions into software products. They collaborate with data scientists, engineers, and stakeholders to solve complex problems and optimize AI algorithms for real-world use. Python AI Developers stay updated on the latest AI techniques and ensure their solutions are efficient, scalable, and maintainable.
Python Ai Developer jobs near you

Machine Learning Engineer

Bespoke Labs

Jackson, MS • On-site

Full-time

Posted 18 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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