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Internship Research Assistant Machine Learning Jobs in Colorado

Bespoke Labs

Machine Learning Engineer

Thornton, CO · On-site

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

Bespoke Labs

Machine Learning Engineer

Aurora, CO · On-site

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

Bespoke Labs

Machine Learning Engineer

Denver, CO · On-site

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

Bespoke Labs

Machine Learning Engineer

Greeley, CO · On-site

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

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Internship Research Assistant Machine Learning information

What are the big 4 internships?

The 'Big 4' internships typically refer to internship programs offered by the four largest professional services firms: Deloitte, PricewaterhouseCoopers (PwC), Ernst & Young (EY), and KPMG. These firms offer internships in areas such as consulting, audit, tax, and advisory, providing valuable experience for aspiring professionals, including those interested in roles like Internship Research Assistant in machine learning if related to data analysis or consulting projects. Securing these internships often requires strong academic performance, relevant skills, and competitive application processes.

Which 5 jobs will survive AI?

For an Internship Research Assistant in Machine Learning, roles that involve complex problem-solving, creativity, and human judgment—such as research scientist, data scientist, AI ethicist, machine learning engineer, and technical project manager—are more likely to persist despite AI advancements. These positions require specialized skills, critical thinking, and collaboration that are difficult for AI to fully replicate. Continuous learning and expertise in tools like Python, TensorFlow, or PyTorch enhance job security in this field.

How to get an AI ML internship?

To secure an AI ML internship, candidates should develop strong programming skills in languages like Python, gain experience with machine learning frameworks such as TensorFlow or PyTorch, and build a portfolio of relevant projects. Applying through company career portals, leveraging university connections, and demonstrating knowledge of data analysis and algorithms can improve chances. Internships often require a background in computer science, mathematics, or related fields, and may involve technical assessments or interviews.

What is the difference between Internship Research Assistant Machine Learning vs Research Assistant Data Science?

AspectInternship Research Assistant Machine LearningResearch Assistant Data Science
Required CredentialsUndergraduate or graduate in CS, AI, or related fieldsUndergraduate or graduate in CS, Statistics, or related fields
Work EnvironmentAcademic labs, research institutions, tech companiesAcademic institutions, research centers, industry
Employer & Industry UsageUniversities, research firms, tech companies focusing on AI/MLUniversities, research organizations, data-driven industries
Common Search & ComparisonYesYes

The Internship Research Assistant Machine Learning and Research Assistant Data Science roles share similarities in educational background and work environments. However, the Machine Learning position emphasizes AI and ML-specific skills, while Data Science focuses more on statistical analysis and data management. Both roles are common in academic and industry settings, often compared by students and professionals exploring research opportunities in data-driven fields.

How much do ML interns get paid?

Machine Learning internship research assistants typically earn between $15 and $30 per hour, depending on the company, location, and level of experience. Paid internships often include opportunities to work with tools like Python and TensorFlow and may be full-time or part-time during the summer or academic year.
What are popular job titles related to Internship Research Assistant Machine Learning jobs in Colorado? For Internship Research Assistant Machine Learning jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Internship Research Assistant Machine Learning jobs in Colorado look for? The top searched job categories for Internship Research Assistant Machine Learning jobs in Colorado are:
What cities in Colorado are hiring for Internship Research Assistant Machine Learning jobs? Cities in Colorado with the most Internship Research Assistant Machine Learning job openings:
Internship Research Assistant Machine Learning jobs near you

Machine Learning Engineer

Bespoke Labs

Thornton, CO • 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

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