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Deep Learning Engineer Jobs in Colorado (NOW HIRING)

Bespoke Labs

Machine Learning Engineer

Thornton, CO · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Denver, CO · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Greeley, CO · On-site

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 ...

Ibotta, Inc

Staff Machine Learning Engineer

Denver, CO · On-site

$206K - $230K/yr

Ibotta is seeking a Staff Machine Learning Engineer to join our Core Data & Analytics team and ... Deep hands-on experience prototyping, building, releasing, and monitoring mission-critical machine ...

Bespoke Labs

Machine Learning Engineer

Aurora, CO · On-site

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 ...

Ibotta

Staff Machine Learning Engineer

Denver, CO · On-site +1

$206K - $230K/yr

Ibotta is seeking a Staff Machine Learning Engineer to join our Core Data & Analytics team and ... Deep hands-on experience prototyping, building, releasing, and monitoring mission-critical machine ...

AppFolio

Staff Machine Learning Engineer

Denver, CO

Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. * Cloud-native engineering: Strong Python, Docker, dependency management, and CI/CD ...

AppFolio

CO

Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. * Cloud-native engineering: Strong Python, Docker, dependency management, and CI/CD ...

SynergisticIT

AI & Machine Learning Engineer

Denver, CO · On-site

$117K - $141K/yr

Deep Learning * Data visualization * NLP * Scala * Django Roles and Responsibilities * Collaborate with dynamic teams of engineers, developers, and scientists who research and integrate algorithms to ...

True Anomaly

Senior Machine Learning Engineer

Denver, CO · On-site

$180K - $360K/yr

You are a first-principles engineer who takes ownership of the systems you build and delivers ... Anomaly & outlier detection: statistical, density-based, and deep learning approaches * Object ...

Booz Allen Hamilton

Computer Vision AI Engineer

Aurora, CO · On-site

$99K - $225K/yr

Develop and implement deep learning computer vision models, with a focus on sensor fusion and ... Utilize GPU programming, including CUDA or RAPIDs, to optimize the performance of computer vision ...

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Deep Learning Engineer information

See Colorado salary details

$40K

$121.8K

$201.4K

How much do deep learning engineer jobs pay per year?

As of Jun 22, 2026, the average yearly pay for deep learning engineer in Colorado is $121,834.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,300.00 and $159,300.00 per year, depending on experience, location, and employer.

What is a Deep Learning Engineer job?

A Deep Learning Engineer is a specialized software engineer who designs, develops, and optimizes deep learning models. They work with neural networks, large datasets, and frameworks like TensorFlow or PyTorch to build AI systems for tasks like image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, performance tuning, and deploying models into production. Strong programming skills in Python, knowledge of machine learning algorithms, and experience with GPU acceleration are essential for this role.

What are the key skills and qualifications needed to thrive in the Deep Learning Engineer position, and why are they important?

To thrive as a Deep Learning Engineer, you need a strong background in mathematics, machine learning theory, and programming (especially Python), often supported by a relevant degree in computer science, engineering, or related fields. Proficiency with frameworks such as TensorFlow, PyTorch, Keras, as well as experience with GPUs and cloud platforms, is highly valued, and certifications in AI or deep learning can further enhance your profile. Effective problem-solving, strong collaboration skills, and clear communication are important soft skills for excelling in interdisciplinary teams. These abilities ensure that you can develop robust deep learning models, adapt to evolving technologies, and contribute value in both technical and collaborative settings.

What are the typical daily tasks and responsibilities of a Deep Learning Engineer?

Deep Learning Engineers typically spend their days designing, developing, and optimizing neural network models for tasks like image recognition, natural language processing, or recommendation systems. They preprocess and analyze large datasets, experiment with model architectures, and tune hyperparameters to achieve the best performance. Collaboration is often required with data scientists, product managers, and software engineers to integrate models into real-world applications and scale solutions for production. Additionally, many deep learning engineers review current research, stay updated on advancements in AI, and continuously improve their skills. This role offers a dynamic work environment where learning and innovation are highly encouraged.

What are the most commonly searched types of Deep Learning Engineer jobs in Colorado? The most popular types of Deep Learning Engineer jobs in Colorado are:
What are popular job titles related to Deep Learning Engineer jobs in Colorado? For Deep Learning Engineer jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Deep Learning Engineer jobs in Colorado look for? The top searched job categories for Deep Learning Engineer jobs in Colorado are:
What cities in Colorado are hiring for Deep Learning Engineer jobs? Cities in Colorado with the most Deep Learning Engineer job openings:
Deep Learning Engineer jobs near you
Infographic showing various Deep Learning Engineer job openings in Colorado as of June 2026, with employment types broken down into 9% Internship, 73% Full Time, and 18% Contract. Highlights an 96% In-person, and 4% Hybrid job distribution, with an average salary of $121,834 per year, or $58.6 per hour.

Machine Learning Engineer

Bespoke Labs

Thornton, CO • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

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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