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Machine Learning Internship No Experience Jobs in Colorado

bet365

Machine Learning Engineer

Denver, CO

$120K - $140K/yr

Proven experience as an ML Engineer, Data Engineer, or Software Engineer with a clear focus on deploying, monitoring, and scaling machine learning systems in production. * A pragmatic, proactive ...

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

Instacart

Instacart is a Flex First team There's no one-size fits all approach to how we do our best work ... Experience in applying machine learning and optimization techniques to solve marketplace problems ...

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Machine Learning Internship No Experience information

What are the key skills and qualifications needed to thrive as a Machine Learning Intern with no prior experience, and why are they important?

To thrive as a Machine Learning Intern with no experience, you need a solid understanding of programming (especially Python), basic statistics, and foundational machine learning concepts, often demonstrated through coursework or personal projects. Familiarity with tools like scikit-learn, TensorFlow, Jupyter Notebooks, and version control systems (e.g., Git) is typically expected. Curiosity, eagerness to learn, problem-solving ability, and effective communication are standout soft skills in this position. These skills and qualities are crucial for adapting quickly, contributing to projects, and maximizing growth in a hands-on learning environment.

What is a machine learning internship with no experience?

A machine learning internship with no experience is an entry-level opportunity designed for students or individuals who are new to the field of machine learning and may not have previous professional experience. These internships typically focus on foundational skills such as data preprocessing, understanding basic algorithms, and using popular tools like Python, TensorFlow, or PyTorch. Interns are often provided with mentorship, training, and real-world projects to help them learn and apply machine learning concepts. The goal is to gain practical experience and build a portfolio, which can be helpful for future job opportunities in the field.

What types of projects or tasks are typically assigned to machine learning interns with no prior experience?

Machine learning interns with no prior experience are often assigned to support tasks such as data preprocessing, exploratory data analysis, and helping to clean or organize datasets. They may also assist with implementing, testing, or tuning basic machine learning models under the guidance of experienced team members. Interns are encouraged to participate in team meetings, contribute to code reviews, and learn about the deployment process, giving them valuable exposure to real-world workflows and collaboration within a machine learning team.

What is the difference between Machine Learning Internship No Experience vs Data Science Intern No Experience?

AspectMachine Learning Internship No ExperienceData Science Intern No Experience
Required CredentialsBasic programming skills, introductory knowledge of ML conceptsBasic programming skills, introductory knowledge of data analysis
Work EnvironmentTech companies, startups, research labsTech companies, consulting firms, research organizations
Employer & Industry UsagePrimarily in AI and ML-focused rolesBroader data analysis and business intelligence roles
Search & Comparison IntentUnderstanding entry-level ML roles for beginnersExploring data analysis internships for beginners

Both internships are entry-level roles requiring foundational skills in programming. Machine Learning Internships focus on developing algorithms and models, while Data Science Internships emphasize data analysis and visualization. The choice depends on your interest in AI/ML versus broader data analysis tasks.

What are popular job titles related to Machine Learning Internship No Experience jobs in Colorado? For Machine Learning Internship No Experience jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Machine Learning Internship No Experience jobs in Colorado look for? The top searched job categories for Machine Learning Internship No Experience jobs in Colorado are:
What cities in Colorado are hiring for Machine Learning Internship No Experience jobs? Cities in Colorado with the most Machine Learning Internship No Experience job openings:
Machine Learning Internship No Experience jobs near you
Infographic showing various Machine Learning Internship No Experience job openings in Colorado as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, and 5% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

bet365

Denver, CO

$120K - $140K/yr

Full-time

Posted 29 days ago

Bet365 rating

9.1

Company rating: 9.1 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

2nd of 15 rated gambling companies

Job description

Company Description

We're one of the world's leading online gambling companies, revolutionising the industry since 2000. Founded by Denise Coates CBE, we now employ over 10,000 people and serve over 120 million customers in 26 languages. 
We empower our employees to push boundaries and explore new ideas, cultivating a culture that celebrates and rewards creativity. This offers employees a wealth of growth opportunities, giving them the opportunity to make a real impact in the world of online gambling. As a forward-thinking company, we're breaking new ground in software innovation too, redefining what's possible for our global worldwide.
Our focus on In-Play betting has solidified our market-leading position, featuring more than 1.38 million In-Play sporting events a year. With over 750 concurrent sporting fixtures at peak and more live sports streamed than anyone else in Europe (750,000), we handle over 6 million HTTP requests daily and process more than 1.5 million bets per hour at peak.

Job Description

We are seeking a highly pragmatic, results-driven Machine Learning (ML) Engineer to join our newly established US Data team. In this role, you will build the reliable, automated infrastructure that powers our machine learning lifecycle.

Your primary mission is to operationalize and scale the models developed by our data science team, taking them from prototype to robust, production-grade systems with high velocity.

You'll focus on building reliable, automated and maintainable systems, keeping solutions pragmatic rather than over-engineered. You will also be passionate about automation, software engineering excellence, and MLOps.

You will report to the Data Science Team Leader and work in close alignment with the US AgentOps Team Lead (responsible for agentic and model orchestration platforms) and our UK technical excellence center. You will act as the bridge between model development and reliable platform engineering.

The listed salary for this position is $120,000 - $140,000 annually.

Qualifications
  • Proven experience as an ML Engineer, Data Engineer, or Software Engineer with a clear focus on deploying, monitoring, and scaling machine learning systems in production.
  • A pragmatic, proactive approach to system design, prioritizing speed, reliability, and business value over complex, theoretical infrastructure.
  • Strong Python programming skills, with a solid grasp of software engineering patterns, API development, and automated testing frameworks.
  • Extensive hands-on experience with Google Cloud Platform (GCP).
  • Practical experience with Vertex AI (specifically Vertex AI Pipelines, Endpoints, and Workbench).
  • Proficiency with containerization (Docker) and container orchestration tools.
  • Excellent communication skills, with the ability to translate software engineering concepts for data scientists and operational requirements for product leads.
  • Experience utilizing Infrastructure as Code (IaC) tools such as Terraform.
  • Experience running containerized workloads on Google Kubernetes Engine (GKE).
  • Familiarity with real-time streaming tools like Apache Kafka or GCP Pub/Sub.
Additional Information
  • Owning the deployment of machine learning models to production. Build and maintain scalable, low-latency prediction endpoints using GCP Vertex AI.
  • Designing, implementing, and maintaining CI/CD/CT (Continuous Integration, Continuous Delivery, Continuous Training) pipelines for machine learning workflows using Vertex AI Pipelines, Cloud Build, and related GCP tools.
  • Setting up automated monitoring and alerting frameworks (e.g., Vertex AI Model Monitoring) to track data drift, model drift, and system performance in real-time.
  • Championing best practices for software engineering within the Data Science team, including robust unit testing, containerization, version control, and CI/CD automation.
  • Working closely with the Data Science Team Leader, Junior Data Scientists, and the AgentOps Team Lead to accelerate deployment cycles, remove operational bottlenecks, and maintain high deployment velocity.

bet365 provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

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