ML Engineer Green Card Jobs
ML Engineer roles qualify for EB-2 sponsorship when the position requires an advanced degree in computer science, statistics, or a related field, and for EB-3 when a bachelor's degree suffices. Employers file PERM labor certification with DOL before petitioning USCIS, making documented specialty-occupation duties and prevailing-wage compliance central to a successful sponsorship.
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Get Access To All JobsWe believe in the power and joy of learning
At Cengage, our employees have a direct impact in helping students around the world discover the power and joy of learning. We are bonded by our shared purpose – driving innovation that helps millions of learners improve their lives and achieve their dreams through education.
Cengage's portfolio of businesses supports student choice by providing a range of pathways that help learners achieve their goals and lead a choice-filled life.
Our culture values inclusion, engagement, and discovery
Our business is driven by our strong culture, and we know that creating an inclusive workplace is absolutely essential to the success of our company and our learners, as well as our individual well-being. We recognize the value of diverse perspectives in everything we do, and strive to ensure employees of all levels and backgrounds feel empowered to voice their ideas and bring their authentic selves to work. We achieve these priorities through programs, benefits, and initiatives that are integrated into the fabric of how we work every day. To learn more, please see https://www.cengagegroup.com/about/inclusion-and-belonging/.
The AI/ML Engineer – Work builds AI-driven workforce and skills-based capabilities for Cengage's career and learning products. You will develop the models and systems that infer skills, verify competencies, and power skills-based matching and recommendations — the capabilities that underpin Cengage's skills graph and workforce platforms including Skills Verification.
This role requires a builder who is excited about applied ML for skills, career, and learning data. The ideal candidate has worked on matching, ranking, recommendation, or representation learning problems, understands the workforce and skills domain, and can ship production ML features that meaningfully improve learner career outcomes.
Key Responsibilities
Skills & Workforce AI Development
- Develop skills inference models that extract competencies from content, assessments, and learner activity
- Build skills verification models powering the Skills Verification platform
- Create skills-based matching and recommendation systems for jobs, courses, and learning paths
- Develop career pathway recommendation and skills gap analysis features
- Integrate AI into Cengage workforce platforms including Infosec Skills and IQ
Platform Integration & Engineering
- Integrate AI into workforce platforms including content, assessment, and lab systems
- Enable skills-based matching and recommendations across Cengage's workforce ecosystem
- Partner with platform engineering on API design, scaling, and production deployment
- Align to the NICE Framework and other recognized skills taxonomies where applicable
- Build evaluation and monitoring systems to measure and improve model accuracy and performance
Measurement & Business Impact
- Track skills verification accuracy, recommendation quality, and adoption of AI-driven career tools
- Partner with product and data science on offline and online evaluation
- Drive integration completeness across Cengage's workforce product suite
- Maintain feature delivery cadence with weekly shipping discipline
- Partner with Governance on patent and IP considerations for novel approaches
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, or related field
- 4+ years of experience in software engineering, with at least 2 years focused on AI/ML
- Strong proficiency in Python with experience building production ML systems
- Hands-on experience with modern ML techniques including embeddings, ranking, and LLMs
- Experience with recommendation systems, matching, or representation learning
- Solid software engineering fundamentals including testing, CI/CD, and system design
- Experience with offline and online model evaluation
- Strong communication skills to work with product, data science, and platform teams
Preferred Qualifications
- Prior experience in workforce tech, HR tech, or skills-based matching platforms
- Familiarity with skills taxonomies (NICE Framework, O*NET, ESCO, Lightcast)
- Experience with LLMs for classification, extraction, and zero-shot matching
- Background in cybersecurity education or adjacent technical learning domains
- Experience with behavioral pattern analysis or competency assessment
- Familiarity with agentic AI frameworks (LangChain, LlamaIndex)
Tools & Technologies
You should be comfortable with many of the following:
- Languages: Python, JavaScript/TypeScript, SQL
- AI/ML: PyTorch, TensorFlow, Hugging Face, OpenAI API, Anthropic API
- ML Infra: AWS SageMaker, MLflow, Weights & Biases, Ray
- Vector DBs: Pinecone, Weaviate, pgvector
- Data: Snowflake, Databricks, Postgres, Spark
- DevOps: Docker, Terraform, GitHub Actions, CI/CD pipelines
Key Competencies
- ML Craft — fluent across classical ML and modern LLM-based approaches
- Product Orientation — connects model improvements to learner and user outcomes
- Shipping Mindset — delivers on weekly cadence with measured impact
- Domain Curiosity — invests in understanding skills, workforce, and career dynamics
- Evaluation Rigor — designs offline and online evaluation thoughtfully
- Collaboration — partners effectively with product, research, and platform engineering
What We Offer
- Opportunity to shape AI at scale across a global learning company
- Direct impact on business outcomes, product, and workforce productivity
- Access to cutting-edge AI tools, platforms, and technologies
- Collaborative team environment focused on innovation and continuous improvement
- Competitive compensation and comprehensive benefits
- Professional development and learning opportunities
Flexible work arrangements with remote/hybrid options
Cengage is committed to working with broad talent pools to attract and hire strong and most qualified individuals. Our job applicants are considered regardless of any classification protected by applicable federal, state, provincial or local laws.
Cengage is also committed to providing reasonable accommodations for qualified individuals with disabilities including during our job application process. If you are an applicant with a disability and require reasonable accommodation in our job application process, please contact us at accommodations.ta@cengage.com.
About Cengage
Cengage, a global education technology company serving millions of learners, provides affordable, quality digital products and services that equip students with the skills and competencies needed to be job ready. For more than 100 years, we have enabled the power and joy of learning with trusted, engaging content, and now, integrated digital platforms. We serve the higher education, workforce skills, secondary education, English language teaching and research markets worldwide. Through our scalable technology, including MindTap and Cengage Unlimited, we support all learners who seek to improve their lives and achieve their dreams through education.
Compensation
At Cengage Group, we take great pride in our commitment to providing a comprehensive and rewarding Total Rewards package designed to support and empower our employees. Click here to learn more about our Total Rewards Philosophy.
The full base pay range has been provided for this position. Individual base pay will vary based on work schedule, qualifications, experience, internal equity, and geographic location. Sales roles often incorporate a significant incentive compensation program beyond this base pay range.
In this position, you will be eligible to participate in the company’s discretionary incentive bonus program. This position's bonus target amount, which is not guaranteed and is dependent on individual performance and overall company results among other factors, is provided below.
10% Annual: Individual Target
$150,000.00 - $200,000.00 USD
We believe in the power and joy of learning
At Cengage, our employees have a direct impact in helping students around the world discover the power and joy of learning. We are bonded by our shared purpose – driving innovation that helps millions of learners improve their lives and achieve their dreams through education.
Cengage's portfolio of businesses supports student choice by providing a range of pathways that help learners achieve their goals and lead a choice-filled life.
Our culture values inclusion, engagement, and discovery
Our business is driven by our strong culture, and we know that creating an inclusive workplace is absolutely essential to the success of our company and our learners, as well as our individual well-being. We recognize the value of diverse perspectives in everything we do, and strive to ensure employees of all levels and backgrounds feel empowered to voice their ideas and bring their authentic selves to work. We achieve these priorities through programs, benefits, and initiatives that are integrated into the fabric of how we work every day. To learn more, please see https://www.cengagegroup.com/about/inclusion-and-belonging/.
The AI/ML Engineer – Work builds AI-driven workforce and skills-based capabilities for Cengage's career and learning products. You will develop the models and systems that infer skills, verify competencies, and power skills-based matching and recommendations — the capabilities that underpin Cengage's skills graph and workforce platforms including Skills Verification.
This role requires a builder who is excited about applied ML for skills, career, and learning data. The ideal candidate has worked on matching, ranking, recommendation, or representation learning problems, understands the workforce and skills domain, and can ship production ML features that meaningfully improve learner career outcomes.
Key Responsibilities
Skills & Workforce AI Development
- Develop skills inference models that extract competencies from content, assessments, and learner activity
- Build skills verification models powering the Skills Verification platform
- Create skills-based matching and recommendation systems for jobs, courses, and learning paths
- Develop career pathway recommendation and skills gap analysis features
- Integrate AI into Cengage workforce platforms including Infosec Skills and IQ
Platform Integration & Engineering
- Integrate AI into workforce platforms including content, assessment, and lab systems
- Enable skills-based matching and recommendations across Cengage's workforce ecosystem
- Partner with platform engineering on API design, scaling, and production deployment
- Align to the NICE Framework and other recognized skills taxonomies where applicable
- Build evaluation and monitoring systems to measure and improve model accuracy and performance
Measurement & Business Impact
- Track skills verification accuracy, recommendation quality, and adoption of AI-driven career tools
- Partner with product and data science on offline and online evaluation
- Drive integration completeness across Cengage's workforce product suite
- Maintain feature delivery cadence with weekly shipping discipline
- Partner with Governance on patent and IP considerations for novel approaches
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, or related field
- 4+ years of experience in software engineering, with at least 2 years focused on AI/ML
- Strong proficiency in Python with experience building production ML systems
- Hands-on experience with modern ML techniques including embeddings, ranking, and LLMs
- Experience with recommendation systems, matching, or representation learning
- Solid software engineering fundamentals including testing, CI/CD, and system design
- Experience with offline and online model evaluation
- Strong communication skills to work with product, data science, and platform teams
Preferred Qualifications
- Prior experience in workforce tech, HR tech, or skills-based matching platforms
- Familiarity with skills taxonomies (NICE Framework, O*NET, ESCO, Lightcast)
- Experience with LLMs for classification, extraction, and zero-shot matching
- Background in cybersecurity education or adjacent technical learning domains
- Experience with behavioral pattern analysis or competency assessment
- Familiarity with agentic AI frameworks (LangChain, LlamaIndex)
Tools & Technologies
You should be comfortable with many of the following:
- Languages: Python, JavaScript/TypeScript, SQL
- AI/ML: PyTorch, TensorFlow, Hugging Face, OpenAI API, Anthropic API
- ML Infra: AWS SageMaker, MLflow, Weights & Biases, Ray
- Vector DBs: Pinecone, Weaviate, pgvector
- Data: Snowflake, Databricks, Postgres, Spark
- DevOps: Docker, Terraform, GitHub Actions, CI/CD pipelines
Key Competencies
- ML Craft — fluent across classical ML and modern LLM-based approaches
- Product Orientation — connects model improvements to learner and user outcomes
- Shipping Mindset — delivers on weekly cadence with measured impact
- Domain Curiosity — invests in understanding skills, workforce, and career dynamics
- Evaluation Rigor — designs offline and online evaluation thoughtfully
- Collaboration — partners effectively with product, research, and platform engineering
What We Offer
- Opportunity to shape AI at scale across a global learning company
- Direct impact on business outcomes, product, and workforce productivity
- Access to cutting-edge AI tools, platforms, and technologies
- Collaborative team environment focused on innovation and continuous improvement
- Competitive compensation and comprehensive benefits
- Professional development and learning opportunities
Flexible work arrangements with remote/hybrid options
Cengage is committed to working with broad talent pools to attract and hire strong and most qualified individuals. Our job applicants are considered regardless of any classification protected by applicable federal, state, provincial or local laws.
Cengage is also committed to providing reasonable accommodations for qualified individuals with disabilities including during our job application process. If you are an applicant with a disability and require reasonable accommodation in our job application process, please contact us at accommodations.ta@cengage.com.
About Cengage
Cengage, a global education technology company serving millions of learners, provides affordable, quality digital products and services that equip students with the skills and competencies needed to be job ready. For more than 100 years, we have enabled the power and joy of learning with trusted, engaging content, and now, integrated digital platforms. We serve the higher education, workforce skills, secondary education, English language teaching and research markets worldwide. Through our scalable technology, including MindTap and Cengage Unlimited, we support all learners who seek to improve their lives and achieve their dreams through education.
Compensation
At Cengage Group, we take great pride in our commitment to providing a comprehensive and rewarding Total Rewards package designed to support and empower our employees. Click here to learn more about our Total Rewards Philosophy.
The full base pay range has been provided for this position. Individual base pay will vary based on work schedule, qualifications, experience, internal equity, and geographic location. Sales roles often incorporate a significant incentive compensation program beyond this base pay range.
In this position, you will be eligible to participate in the company’s discretionary incentive bonus program. This position's bonus target amount, which is not guaranteed and is dependent on individual performance and overall company results among other factors, is provided below.
10% Annual: Individual Target
$150,000.00 - $200,000.00 USD
See all 3,883+ ML Engineer jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new ML Engineer roles.
Get Access To All JobsTips for Finding Green Card Sponsorship as a ML Engineer
Document your ML specialization before applying
PERM requires your employer to prove the role needs your specific qualifications. Compile publications, model deployment records, and performance benchmarks that tie your ML credentials to the job duties your employer will list on the labor certification.
Target employers with dedicated immigration infrastructure
Large tech firms and research-driven companies with in-house immigration counsel move PERM cases faster and with fewer errors. Look for ML roles at organizations that have sponsored foreign workers before, not just those posting open positions.
Search green card sponsoring ML jobs on Migrate Mate
Filter by EB-2 or EB-3 sponsorship history to find ML Engineer roles at employers who have actually filed PERM cases. Migrate Mate surfaces this DOL disclosure data so you skip the manual search through raw government filings.
Understand the prevailing wage before negotiating your offer
DOL sets four wage levels for ML Engineer roles by location. Use the OFLC Wage Search to check the Level II or Level III rate for your target metro area before your offer conversation, since your salary must meet or exceed the certified wage.
Ask your employer about EB-2 versus EB-3 at the offer stage
If your role genuinely requires a master's degree or you hold a strong credentials profile, EB-2 often means a shorter priority date wait for most nationalities. Clarify which category your employer intends to file under before you accept the offer.
Plan for the PERM recruitment audit window
DOL requires your employer to conduct good-faith recruitment and retain records for five years in case of an audit. Delays in starting that recruitment phase are the most common reason PERM timelines slip, so confirm your employer has begun the process.
ML Engineer jobs are hiring across the US. Find yours.
Find ML Engineer JobsML Engineer Green Card Sponsorship: Frequently Asked Questions
Does an ML Engineer role qualify for EB-2 or EB-3 green card sponsorship?
Most ML Engineer positions qualify for EB-2 because employers routinely require a master's degree or equivalent in computer science, machine learning, or statistics. If the posted job description accepts a bachelor's degree, your employer will file under EB-3 instead. The distinction matters for priority date wait times, which vary significantly by your country of birth.
How does green card sponsorship differ from H-1B for ML Engineer roles?
Green card sponsorship through PERM and an I-140 petition leads to permanent residency, not a temporary work visa. There is no annual lottery for EB-3 the way there is for H-1B, and once your I-140 is approved your priority date is locked even if you change employers under portability rules. The tradeoff is a longer overall timeline, often two to five years from PERM filing to a green card in hand for most nationalities.
What does the PERM labor certification process look like for ML Engineer jobs?
Your employer files a PERM application with DOL certifying that no qualified U.S. worker was available for the ML Engineer role at the prevailing wage. DOL requires a specific recruitment campaign before filing, including job postings and documentation of applicant review. Once DOL certifies the PERM, your employer files the I-140 immigrant petition with USCIS, which locks in your priority date.
How can I find ML Engineer jobs where the employer will sponsor a green card?
Search for ML Engineer roles on Migrate Mate, which filters positions by employers with confirmed EB-2 and EB-3 PERM filing history drawn from DOL disclosure data. This removes the guesswork of cold-applying to companies that have never sponsored a foreign worker, letting you focus your effort on employers who have already run the process.
Can I use O*NET to confirm whether my ML Engineer duties support a specialty occupation?
Yes. The O*NET profile for ML Engineer and related data science occupations lists the typical education requirements, core tasks, and required knowledge areas that DOL and USCIS use when evaluating specialty occupation and PERM eligibility. If your day-to-day duties align closely with the O*NET task list, your employer's labor certification case is on stronger footing.
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