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Entry Level Machine Learning Engineer Jobs in Broomfield, CO

Machine Learning Engineer

Denver, CO · On-site

$120K - $140K/yr

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 ...

Entry Level Machine Operator

Golden, CO · On-site

$16.75 - $20.50/hr

Job Title Entry Level Machine Operator Job Summary We are hiring Entry Level Machine Operators to ... learning valuable skills in machine operation, quality control, and industrial processes. Key ...

Entry Level Machine Operator

Golden, CO

$16.75 - $20.50/hr

Job Title Entry Level Machine Operator Job Summary We are hiring Entry Level Machine Operators to ... learning valuable skills in machine operation, quality control, and industrial processes. Key ...

Who We Are Looking For We're hiring a Staff Machine Learning Engineer to help move forward the ML platform that every AI initiative at AppFolio depends on -- training, fine-tuning, inference, RAG ...

That's why we need you, an experienced machine learning engineer, to help us design and architect an MLOps platform in the Cloud that shortens the time it takes to get new capabilities from ...

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Showing results 1-20

Entry Level Machine Learning Engineer information

See Broomfield, CO salary details

$30.2K

$69.9K

$118.9K

How much do entry level machine learning engineer jobs pay per year?

As of Jul 31, 2026, the average yearly pay for entry level machine learning engineer in Broomfield, CO is $69,887.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,900.00 and $79,100.00 per year, depending on experience, location, and employer.

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

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an Entry Level Machine Learning Engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What is an Entry Level Machine Learning Engineer job?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are popular job titles related to Entry Level Machine Learning Engineer jobs in Broomfield, CO? For Entry Level Machine Learning Engineer jobs in Broomfield, CO, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning Engineer jobs in Broomfield, CO look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in Broomfield, CO are:
What cities near Broomfield, CO are hiring for Entry Level Machine Learning Engineer jobs? Cities near Broomfield, CO with the most Entry Level Machine Learning Engineer job openings:
Infographic showing various Entry Level Machine Learning Engineer job openings in Broomfield, CO as of July 2026, with employment types broken down into 1% Locum Tenens, 93% Full Time, 4% Part Time, and 2% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $69,887 per year, or $33.6 per hour.

Machine Learning Engineer

bet365

Denver, CO • On-site

$120K - $140K/yr

Full-time

Re-posted yesterday


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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