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Associate Full Stack Machine Learning Engineer Jobs in Colorado

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 ...

Full ML lifecycle: Strong understanding of data extraction, model training, evaluation, deployment ... Core stack: Expert in Python, PyTorch, NumPy, AWS, Docker, SQL, embeddings, and RAG. * Agent ...

Senior AI/Machine Learning Engineer

Denver, CO · On-site +1

$126K - $166K/yr

We're looking for a hands-on Senior AI/Machine Learning Engineer to design, build, and deploy AI ... Strong Python and the modern ML stack (PyTorch or TensorFlow, scikit-learn), plus solid SQL.

Senior AI/Machine Learning Engineer

Denver, CO · On-site +1

$126K - $166K/yr

We're looking for a hands-on Senior AI/Machine Learning Engineer to design, build, and deploy AI ... Strong Python and the modern ML stack (PyTorch or TensorFlow, scikit-learn), plus solid SQL.

Senior Machine Learning Engineer I // II

Denver, CO · On-site +1

$107K - $147K/yr

The Senior Machine Learning Engineer will join our ML team. This team is responsible for building ... Stack: Proficiency in Python , SQL, key ML libraries, and Spark * Mindset: A strong outcome ...

Senior AI/Machine Learning Engineer

Denver, CO · On-site +1

$126K - $166K/yr

We're looking for a hands-on Senior AI/Machine Learning Engineer to design, build, and deploy AI ... Strong Python and the modern ML stack (PyTorch or TensorFlow, scikit-learn), plus solid SQL.

We are hiring a Full Stack Engineer to join our centralized team in the Denver Tech Center, CO ... A growth-oriented mindset with enthusiasm for learning and adapting. Additional Information AIR ...

Sr. Machine Learning Engineer

Denver, CO

$107K - $147K/yr

... full context of property management workflows. This foundation allows us to build context-aware ... Voice stack: Hands-on with Voice-to-Voice models and traditional TTS / STT pipelines; understands ...

CO

$107K - $147K/yr

... full context of property management workflows. This foundation allows us to build context-aware ... Voice stack: Hands-on with Voice-to-Voice models and traditional TTS / STT pipelines; understands ...

Senior Machine Learning Engineer

Denver, CO · On-site

$180K - $360K/yr

... machine learning and AI capabilities for True Anomaly. You will work with a talented cross ... Own the full ML development lifecycle - from data ingestion and feature engineering through model ...

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Associate Full Stack Machine Learning Engineer information

What are the most commonly searched types of Full Stack Machine Learning Engineer jobs in Colorado? The most popular types of Full Stack Machine Learning Engineer jobs in Colorado are:
What cities in Colorado are hiring for Associate Full Stack Machine Learning Engineer jobs? Cities in Colorado with the most Associate Full Stack Machine Learning Engineer job openings:

Full-time

Posted 4 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