ML Software Engineer Visa Sponsorship Jobs in Colorado
ML software engineer visa sponsorship jobs in Colorado are concentrated in Denver and Boulder, where companies like Google, Amazon, and Palantir maintain active ML teams. The state's growing aerospace and defense sector, alongside a strong university pipeline from CU Boulder and Colorado State, makes it a consistent source of H-1B visa sponsoring employers across applied ML and research roles.
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Get Access To All JobsData Scientist
On-site in Longmont, Colorado. Monday through Friday, business hours, Mountain Time.
About Docketly
Docketly, a sister company to ABC Legal Services, is a fast-growing legal-tech company based in Longmont, Colorado. For the creditors' rights industry, we make hiring a stand-in attorney easy, fast, and reliable. We pair proprietary software with a nationwide network of attorneys.
Job Overview
You build and run the machine learning and analytics systems behind Docketly's operations. You build and run production models, from first idea to a live, monitored system on AWS. ABC Legal's data science team is your sounding board on methods. You build the BI reporting that leadership, operations, and client teams use daily. You support pricing and margin decisions with financial modeling. You work closely with backend engineers on data infrastructure and production issues. This role can grow into Senior Data Scientist as you take full ownership of the production model and the pricing roadmap.
Key Responsibilities
Model development and MLOps
- Build and run the full lifecycle of production ML models: framing, feature engineering, training, validation, deployment on AWS SageMaker (Model Registry, real-time endpoints), inference infrastructure (for example, AWS Lambda), and ongoing monitoring.
- Build and maintain automated retraining and drift monitoring for deployed models.
- Run staged production rollouts with holdout comparisons to prove model impact before full release. Review the test design with the team before launch.
- Use AI coding tools to speed up analysis, modeling, and MLOps work.
Analytics, pricing, and reporting
- Build and maintain the BI layer leadership relies on for exec reporting on revenue, margin, and volume, from dashboard design through data accuracy.
- Run pricing and margin analysis for client accounts, including ad hoc investigations for named strategic accounts. Model the financial impact of proposed pricing changes before they go live.
- Build and maintain rules-based pricing and case-difficulty logic by court and county, alongside statistical and ML approaches.
- Build and tune large scoring and prioritization frameworks in Metabase, such as weighting, percentile scenarios, and drop-rate analysis, that drive daily operational decisions such as Hearing priority and assignment.
- Turn ambiguous business questions into clear, well-scoped analyses.
Cross-functional partnership and documentation
- Partner with engineering on data pipelines (AWS Glue, Lambda, EventBridge). Investigate and help resolve production database performance issues, such as ORM query patterns and indexing, alongside backend engineering.
- Write down your methods and decisions in Confluence or an equivalent shared space, as you go, so other teams can find your reasoning and build on it without asking you directly.
Systems & Skills
Required
- Bachelor's degree in a related field, or equivalent practical experience, and 3+ years of experience with applied statistics or machine learning.
- Applied statistics: probability, hypothesis testing, and model evaluation across classification and regression/quantile models (for example, precision, recall, calibration, quantile coverage, and drift).
- 3+ years of experience with SQL and a relational database in a professional capacity. Docketly's production database runs on MySQL/Aurora, about 400 tables.
- Python for data analysis and modeling: pandas, scikit-learn, and a gradient-boosting framework (XGBoost, LightGBM, or CatBoost). Our production model uses CatBoost-based quantile regression.
- Experience training and deploying at least one model to production, or on a cloud ML platform such as AWS SageMaker.
- Metabase or comparable BI tooling.
- Clear written and verbal communication with non-technical stakeholders.
Preferred
- Staged production rollouts (canary or phased release) with holdout comparisons to prove model impact before full release.
- AWS Glue, S3, Lambda, EventBridge, CloudFormation.
- Comfortable using AI coding tools such as Claude Code or GitHub Copilot to move faster on analysis and modeling work.
- Experience diagnosing production database performance issues, such as query plans, indexing, and ORM-generated query patterns, in a large, high-table-count schema.
- Software-engineering practices applied to ML code, such as automated testing with pytest, for production pipelines.
Benefits
- Health, Dental, and Vision Insurance
- 401(k) with Company Matching
- Paid Time Off
- 7 Paid Company Holidays
- 4 Floating Holidays per Year
- Life Insurance and AD&D Insurance
- Long-Term Disability
- Health Care Reimbursement Flexible Spending Account (FSA)
- Dependent Care Flexible Spending Account
- Employee Assistance Program (EAP)
- Pet Insurance
Schedule & Location
Schedule: Monday-Friday, 8:00 AM-5:00 PM (Mountain Time) in Longmont, CO.
Salary Range: $110,000-$130,000 depending on experience
Application closing date: November 20, 2026, at 11:59pm
Data Scientist
On-site in Longmont, Colorado. Monday through Friday, business hours, Mountain Time.
About Docketly
Docketly, a sister company to ABC Legal Services, is a fast-growing legal-tech company based in Longmont, Colorado. For the creditors' rights industry, we make hiring a stand-in attorney easy, fast, and reliable. We pair proprietary software with a nationwide network of attorneys.
Job Overview
You build and run the machine learning and analytics systems behind Docketly's operations. You build and run production models, from first idea to a live, monitored system on AWS. ABC Legal's data science team is your sounding board on methods. You build the BI reporting that leadership, operations, and client teams use daily. You support pricing and margin decisions with financial modeling. You work closely with backend engineers on data infrastructure and production issues. This role can grow into Senior Data Scientist as you take full ownership of the production model and the pricing roadmap.
Key Responsibilities
Model development and MLOps
- Build and run the full lifecycle of production ML models: framing, feature engineering, training, validation, deployment on AWS SageMaker (Model Registry, real-time endpoints), inference infrastructure (for example, AWS Lambda), and ongoing monitoring.
- Build and maintain automated retraining and drift monitoring for deployed models.
- Run staged production rollouts with holdout comparisons to prove model impact before full release. Review the test design with the team before launch.
- Use AI coding tools to speed up analysis, modeling, and MLOps work.
Analytics, pricing, and reporting
- Build and maintain the BI layer leadership relies on for exec reporting on revenue, margin, and volume, from dashboard design through data accuracy.
- Run pricing and margin analysis for client accounts, including ad hoc investigations for named strategic accounts. Model the financial impact of proposed pricing changes before they go live.
- Build and maintain rules-based pricing and case-difficulty logic by court and county, alongside statistical and ML approaches.
- Build and tune large scoring and prioritization frameworks in Metabase, such as weighting, percentile scenarios, and drop-rate analysis, that drive daily operational decisions such as Hearing priority and assignment.
- Turn ambiguous business questions into clear, well-scoped analyses.
Cross-functional partnership and documentation
- Partner with engineering on data pipelines (AWS Glue, Lambda, EventBridge). Investigate and help resolve production database performance issues, such as ORM query patterns and indexing, alongside backend engineering.
- Write down your methods and decisions in Confluence or an equivalent shared space, as you go, so other teams can find your reasoning and build on it without asking you directly.
Systems & Skills
Required
- Bachelor's degree in a related field, or equivalent practical experience, and 3+ years of experience with applied statistics or machine learning.
- Applied statistics: probability, hypothesis testing, and model evaluation across classification and regression/quantile models (for example, precision, recall, calibration, quantile coverage, and drift).
- 3+ years of experience with SQL and a relational database in a professional capacity. Docketly's production database runs on MySQL/Aurora, about 400 tables.
- Python for data analysis and modeling: pandas, scikit-learn, and a gradient-boosting framework (XGBoost, LightGBM, or CatBoost). Our production model uses CatBoost-based quantile regression.
- Experience training and deploying at least one model to production, or on a cloud ML platform such as AWS SageMaker.
- Metabase or comparable BI tooling.
- Clear written and verbal communication with non-technical stakeholders.
Preferred
- Staged production rollouts (canary or phased release) with holdout comparisons to prove model impact before full release.
- AWS Glue, S3, Lambda, EventBridge, CloudFormation.
- Comfortable using AI coding tools such as Claude Code or GitHub Copilot to move faster on analysis and modeling work.
- Experience diagnosing production database performance issues, such as query plans, indexing, and ORM-generated query patterns, in a large, high-table-count schema.
- Software-engineering practices applied to ML code, such as automated testing with pytest, for production pipelines.
Benefits
- Health, Dental, and Vision Insurance
- 401(k) with Company Matching
- Paid Time Off
- 7 Paid Company Holidays
- 4 Floating Holidays per Year
- Life Insurance and AD&D Insurance
- Long-Term Disability
- Health Care Reimbursement Flexible Spending Account (FSA)
- Dependent Care Flexible Spending Account
- Employee Assistance Program (EAP)
- Pet Insurance
Schedule & Location
Schedule: Monday-Friday, 8:00 AM-5:00 PM (Mountain Time) in Longmont, CO.
Salary Range: $110,000-$130,000 depending on experience
Application closing date: November 20, 2026, at 11:59pm
ML Software Engineer Job Roles in Colorado
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Search ML Software Engineer Jobs in ColoradoML Software Engineer Jobs in Colorado: Frequently Asked Questions
Which companies sponsor visas for ml software engineers in Colorado?
Google's Boulder engineering office, Amazon Web Services, Palantir Technologies (headquartered in Denver), and Lockheed Martin's Colorado operations have all filed H-1B petitions for ML-related roles. Larger enterprise tech firms and defense contractors in the Denver metro tend to have established sponsorship processes, while smaller startups in the Boulder ecosystem may sponsor selectively depending on the seniority and specialization of the role.
Which visa types are most common for ml software engineer roles in Colorado?
The H-1B is by far the most common visa for ML software engineers in Colorado, as the role typically qualifies as a specialty occupation requiring at least a bachelor's degree in computer science, machine learning, or a closely related field. Candidates with exceptional research credentials may also see O-1A petitions used by employers. Australians working in Colorado can pursue the E-3 visa, which operates outside the H-1B lottery.
Which cities in Colorado have the most ml software engineer sponsorship jobs?
Denver and Boulder account for the large majority of ML software engineer sponsorship activity in Colorado. Denver draws employers in finance, aerospace, and enterprise software, while Boulder has a denser concentration of deep tech and AI-focused companies, partly driven by proximity to CU Boulder. Colorado Springs has a smaller but growing presence through defense contractors with ML and computer vision requirements.
How to find ml software engineer visa sponsorship jobs in Colorado?
Migrate Mate filters job listings specifically for roles that include visa sponsorship, so you can search ML software engineer positions in Colorado without sorting through postings that won't support international candidates. Because sponsorship willingness isn't always stated clearly in generic job boards, Migrate Mate's focus on sponsoring employers saves significant time for candidates targeting Colorado's Denver and Boulder ML hiring markets.
Are there any Colorado-specific factors ml software engineers should know about when seeking visa sponsorship?
Colorado's Equal Pay for Equal Work Act requires employers to disclose compensation ranges in job postings, which gives international candidates more transparency when evaluating whether a role meets H-1B prevailing wage requirements before applying. CU Boulder and Colorado State University also generate a consistent pipeline of OPT candidates, meaning local employers are generally more familiar with work authorization processes than employers in states with less university-driven international hiring.
What is the prevailing wage for sponsored ml software engineer jobs in Colorado?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.