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Junior Aws Machine Learning Jobs in Colorado (NOW HIRING)

Socket.dev

Machine Learning Engineer

Colorado Springs, CO · On-site

$135.15 - $225/hr

We are seeking a Machine Learning Engineer to lead the design, development, and deployment of ... Strong understanding of data structures, SQL, and cloud platforms (e.g., AWS SageMaker, Azure ML ...

Cymertek

Machine Learning Engineer

Aurora, CO · On-site

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Capital Rx

Senior Machine Learning Engineer

Denver, CO · On-site

$161K - $202K/yr

We are looking for an experienced software engineer with machine learning expertise to join us in ... Familiarity with cloud platforms such as AWS or Azure. * Familiarity with GenAI services such as ...

Bespoke Labs

Machine Learning Engineer

Aurora, CO · On-site

... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

Bespoke Labs

Machine Learning Engineer

Thornton, CO · On-site

... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

Bespoke Labs

Machine Learning Engineer

Denver, CO · On-site

... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

Bespoke Labs

Machine Learning Engineer

Greeley, CO · On-site

... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

Capital Rx

Senior Machine Learning Engineer II

Denver, CO · On-site

$180K - $225K/yr

Design, develop, and productionize machine learning (ML) solutions in the fields of Document ... Familiarity with cloud platforms such as AWS or Azure. * Familiarity with GenAI services such as ...

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Junior Aws Machine Learning information

What is a junior AWS machine learning engineer?

Junior AWS Machine Learning engineers are entry-level professionals who work with Amazon Web Services (AWS) to develop, deploy, and maintain machine learning models. They assist in data preparation, model training, and integration of AI solutions using AWS tools such as SageMaker, Lambda, and S3. These engineers often collaborate with data scientists and software teams to implement predictive analytics and automation solutions on the AWS cloud platform. Their role typically involves learning best practices for cloud security, data handling, and scalable machine learning deployment.

What are the key skills and qualifications needed to thrive as a junior AWS machine learning engineer?

To thrive as a Junior AWS Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of machine learning concepts, and a relevant degree in computer science or a related field. Familiarity with AWS services like SageMaker, Lambda, and S3, as well as certifications such as AWS Certified Machine Learning – Specialty, are highly valuable. Strong problem-solving skills, attention to detail, and the ability to communicate technical ideas clearly help you stand out in this role. These skills and qualities are crucial for efficiently developing, deploying, and maintaining machine learning solutions on AWS in collaborative, fast-paced environments.

Are there entry level AWS jobs?

Yes, there are entry-level AWS jobs such as Junior AWS Machine Learning roles that typically require foundational knowledge of cloud computing, basic understanding of machine learning concepts, and familiarity with AWS services like S3, EC2, and SageMaker. These roles often serve as starting points for careers in cloud and machine learning fields and may require certifications like AWS Certified Cloud Practitioner or AWS Certified Machine Learning – Specialty. Candidates should be prepared to learn on the job and develop skills through training and hands-on experience.

What are some common challenges faced by junior AWS machine learning engineers when deploying models to production environments?

Junior AWS Machine Learning Engineers often encounter challenges such as managing the scalability of their models, ensuring data security and compliance in the cloud, and integrating machine learning pipelines with existing AWS services. Since production environments require high reliability, newcomers may also need to learn how to monitor model performance and troubleshoot issues using AWS tools like SageMaker and CloudWatch. Collaborating closely with data engineers and DevOps teams is essential to streamline deployment and maintain model accuracy over time.

What is the difference between Junior Aws Machine Learning vs Data Scientist?

AspectJunior Aws Machine LearningData Scientist
Required CredentialsBasic AWS certifications, entry-level ML knowledgeAdvanced degrees, certifications like AWS, data analysis skills
Work EnvironmentCloud platforms, machine learning projects, collaborative teamsData analysis, modeling, research, cross-functional teams
Employer & Industry UsageTech companies, startups, cloud service providersFinance, healthcare, tech, research institutions

Junior AWS Machine Learning roles focus on implementing ML models using AWS tools with foundational knowledge, while Data Scientists typically handle broader data analysis, modeling, and research tasks. The roles overlap in cloud-based ML work but differ in scope and experience level.

What are the most commonly searched types of Aws Machine Learning jobs in Colorado? The most popular types of Aws Machine Learning jobs in Colorado are:
What are popular job titles related to Junior Aws Machine Learning jobs in Colorado? For Junior Aws Machine Learning jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Junior Aws Machine Learning jobs in Colorado look for? The top searched job categories for Junior Aws Machine Learning jobs in Colorado are:
What cities in Colorado are hiring for Junior Aws Machine Learning jobs? Cities in Colorado with the most Junior Aws Machine Learning job openings:
Junior Aws Machine Learning jobs near you

Machine Learning Engineer

Socket.dev

Colorado Springs, CO • On-site

$135.15 - $225/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 days ago

Job description

Overview

Keysight is on the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.


Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.


We are seeking a Machine Learning Engineer to lead the design, development, and deployment of scalable machine learning models that power business decisions across the enterprise. This role combines technical depth in ML/AI with a strong understanding of business domains such as Sales, Service, Finance, Order Fulfillment, and Supply Chain. You will collaborate closely with Data Scientists, Data Engineers, and business partners to build production-ready solutions that drive measurable impact.


Responsibilities

  • Machine Learning Development & Deployment

  • Design and implement supervised and unsupervised models for predictive analytics, including churn prediction, demand forecasting, renewal risk scoring, and cross-sell/upsell opportunity identification.

  • Translate business problems into ML frameworks and production solutions that improve efficiency, revenue, or customer experience.

  • Build, optimize, and maintain ML pipelines using tools such as MLflow, Airflow, or Kubeflow.

  • Cross-Functional ML Use Cases

  • Partner with teams across Sales (e.g., lead scoring, next-best action), Customer Service (e.g., case deflection, sentiment analysis), Finance (e.g., revenue forecasting, fraud detection), Supply Chain (e.g., inventory optimization, ETA prediction), and Order Fulfillment (e.g., delivery risk modeling) to define impactful ML use cases.

  • Develop domain-specific models and continuously improve them using feedback loops and real-world performance data.

  • Model Governance and MLOps

  • Ensure robust model monitoring, versioning, and retraining strategies to keep models reliable in dynamic environments.

  • Work closely with DevOps and Data Engineering teams to automate deployment, CI/CD workflows, and cloud-native ML infrastructure (AWS/GCP/Azure).

  • Data Engineering and Feature Architecture

  • Collaborate with data engineers to define feature stores, data quality checks, and model-ready datasets on platforms like Snowflake or Databricks.

  • Perform feature selection, transformation, and engineering aligned with each domain’s business logic.

  • Communication & Stakeholder Collaboration

  • Present technical insights and model results to business and executive stakeholders in a clear, actionable format.

  • Work with Product Owners and Program Managers to scope, prioritize, and plan delivery of ML projects.


Qualifications

Required:



  • 4-6 years of experience in machine learning, data science, or AI engineering, with a strong software engineering foundation.

  • Proficiency in Python, and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar.

  • Experience deploying models into production using ML pipelines and orchestration frameworks.

  • Strong understanding of data structures, SQL, and cloud platforms (e.g., AWS SageMaker, Azure ML, or GCP Vertex AI).


Preferred

  • Experience supporting business functions such as Finance, Sales, or Operations with ML use cases.

  • Familiarity with MLOps tools (MLflow, SageMaker Pipelines, Feature Store).

  • Exposure to enterprise data platforms (e.g., Snowflake, Oracle Fusion, Salesforce).

  • Background in statistics, forecasting, optimization, or recommendation systems.


Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***


California Pay range

  • MIN $145,970.00 - MAX $266,930.00

  • Colorado pay range: MIN $135,150.00- MAX $225,250.00

  • District of Columbia pay range: MIN $135,150.00- MAX $225,250.00

  • Hawaii pay range: MIN $135,150.00- MAX $225,250.00

  • Illinois pay range: MIN $135,150.00- MAX $225,250.00

  • Maryland pay range: MIN $135,150.00- MAX $225,250.00

  • Massachusetts pay range: MIN $145,970.00 - MAX $243,280.00

  • Minnesota pay range: MIN $135,150.00- MAX $225,250.00

  • New Jersey City pay range: MIN $145,970.00 - MAX $243,280.00

  • New York pay range: MIN $160,160.00 - MAX $266,930.00

  • Vermont pay range: MIN $135,150.00- MAX $225,250.00

  • Washington state pay range: MIN $145,970.00 - MAX $243,280.00


Note:


For other locations, pay ranges will vary by region


US Employees May Be Eligible For The Following Benefits

  • Medical, dental and vision

  • Health Savings Account

  • Health Care and Dependent Care Flexible Spending Accounts

  • Life, Accident, Disability insurance

  • Business Travel Accident and Business Travel Health

  • 401(k) Plan

  • Flexible Time Off, Paid Holidays

  • Paid Family Leave

  • Discounts, Perks

  • Tuition Reimbursement

  • Adoption Assistance

  • ESPP (Employee Stock Purchase Plan)

  • Restricted Stock Units

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