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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

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 ...

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 ...

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 ...

AppFolio

Staff Machine Learning Engineer

Denver, CO · On-site

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 ...

Blissway Inc

Machine Learning Engineer

Denver, CO · On-site

$145K - $195K/yr

Deep Tech, AI/ML, Hardware, SaaS, and IoT. For the past five years, we have built a nearly ... Machine Learning Engineer The Mission: You are the engineer who ships the model, not just the one ...

Blissway Inc.

Machine Learning Engineer

Denver, CO · On-site

$120 - $180/hr

Deep Tech, AI/ML, Hardware, SaaS, and IoT. For the past five years, we have built a nearly ... Machine Learning Engineer The Mission: You are the engineer who ships the model, not just the one ...

Crowe LLP

Machine Learning Engineer

Denver, CO · On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or ... Crowe uses its deep industry expertise to provide audit services to public and private entities ...

Judge Group, Inc.

Principal AI/ML Engineer

Englewood, CO · On-site

$75 - $80.15/hr

Lead the design and development of advanced AI solutions including deep learning, reinforcement ... Guide engineering trade studies, technology selection, and system-level design decisions. AI/ML ...

S Linx LLC

Sr AI Engineer

Greenwood Village, CO · On-site

$105K - $145K/yr

Greenwood Village, CO Duration: Long Term Required Skills: · Hands-on AI/ML leader with strong experience in AI Engineering, Machine Learning, Data Science, or applied NLP / LLM · Deep expertise in ...

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All JobsDeep Learning Engineer JobsDeep Learning Engineer Jobs in Colorado

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 Aug 20, 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?

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 does a deep learning engineer do?

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 skills and qualifications does a deep learning engineer need?

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.

Are deep learning engineers in demand?

Deep learning engineers are in high demand due to the growth of artificial intelligence and machine learning applications across industries such as technology, healthcare, and finance. They typically require skills in neural networks, programming languages like Python, and frameworks such as TensorFlow or PyTorch, with job opportunities increasing as AI adoption expands.

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 August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote 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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