Machine Learning Jobs
Machine learning jobs are open across technology, finance, healthcare, and autonomous systems, from new-grad engineer to principal and staff levels, with specializations in natural language processing, computer vision, and reinforcement learning. Find a role that fits from the openings below and apply directly.
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Showing 5 of 2,403+ Machine Learning jobs
Job Description:
Integral Ad Science (IAS) is a global technology and data company that builds verification, optimization, and analytics solutions for the advertising industry, and we’re looking for a Staff Machine Learning Engineer on the Data Science Team. If you are excited by technology that has the power to handle hundreds of thousands of transactions per second; collect tens of billions of events each day; and evaluate thousands of data points in real-time all while responding in just a few milliseconds, then IAS is the place for you!
As a Staff Machine Learning Engineer at IAS, you will be part of a team that is at the center of innovation for the company and a major contributor to our core products. You will oversee a sophisticated suite of data science systems making large-scale business predictions across the open web, social networks, video, and mobile apps. At the Staff level, you are expected to be a technical pillar for the organization. You will take ownership of open, highly ambiguous business problems and translate them into scalable ML architectures. You will define technical roadmaps, set the standard for ML engineering practices, and push the boundaries of applied machine learning to deliver best-in-class solutions for our clients. Innovation is at the heart of our competitive advantage, and you will cultivate it by mentoring talent and raising the technical bar across multiple teams. The types of challenges we solve have attracted people from industry and academia with diverse backgrounds. We’re passionate about maintaining an open and collaborative environment, where team members bring their own unique style of thinking and tools to the table.
What you’ll get to do:
- Technical Leadership & Vision: Drive the architectural vision and system design for our core AI/ML-based services.
- Act as the technical lead for complex, multi-quarter initiatives from inception to global deployment.
- Architect at Scale: Design and build large-scale deep learning infrastructure and platforms for distributed model training, ensuring low-latency and high-availability at enterprise scale.
- Cross-Functional Influence: Partner with Product Management, Core Engineering, and executive stakeholders to align ML capabilities with business strategy.
- Translate abstract product requirements into concrete technical designs.
- Act as a Multiplier: Mentor and guide senior and mid-level data scientists and engineers.
- Establish standard methodologies, define code quality expectations, and lead architecture design reviews.
- Infrastructure Mastery: Work with large-scale AI training infra components (accelerators, network fabrics, CUDA, NCCL, RDMA) and big data ecosystems (Databricks, Spark, Kubernetes, Kafka, Prometheus).
- End-to-End Ownership: Design, develop, and support robust CI/CD pipelines for AI/ML services, ensuring models transition smoothly from research into reliable production endpoints.
You should apply if you have most of this experience:
- PhD/Master’s degree in a technical field such as computer science, mathematics, statistics, or equivalent years of experience.
- 7+ years of machine learning experience in industry, with a proven track record of operating at a Lead, Principal, or Staff level.
- System Design & Architecture: Deep expertise in designing complex machine learning systems, ranking infrastructures, and data pipelines that handle massive throughput.
- ML Frameworks: Extensive, production-hardened experience working with frameworks such as PyTorch, JAX, or TensorFlow.
- Production Coding: Strong, production-grade programming skills in Python, Go, Java, or C++, along with a deep understanding of software design principles and algorithms.
- Ambiguity & Execution: Proven ability to thrive in ambiguity, take large unstructured problems, and independently drive them to successful technical resolutions.
- Mentorship: A strong history of collaborating with, elevating, and mentoring engineering talent.
IAS Pay Transparency:
The annualized base salary ranges for the primary location, and any additional locations are listed below. Our pay ranges are based on the work location. As part of IAS compensation package, we offer a comprehensive benefits package that includes paid time off, health insurance (medical, dental, vision) as well as PPO, HSA and FSA options and 401k with employer matching contributions. All full-time employee roles include competitive compensation and are eligible for an annual bonus and/or other incentive plans. Each candidate’s compensation package is based on multiple factors, but not limited to, geography, experience, skills, job duties, and business need.
Primary Location:
US - New York, NY
Primary Location Base Pay Range:
$135,100.00 - $231,600.00 Annual
Additional Locations:
USA - Remote
Additional Locations Pay Range:
$119,000.00 - $204,000.00 USD Annual
About Integral Ad Science:
Integral Ad Science (IAS) is a leading global media measurement and optimization platform that delivers the industry’s most actionable data to drive superior results for the world’s largest advertisers, publishers, and media platforms. IAS’s software provides comprehensive and enriched data that ensures ads are seen by real people in safe and suitable environments, while improving return on ad spend for advertisers and yield for publishers. Our mission is to be the global benchmark for trust and transparency in digital media quality. For more information, visit integralads.com.
Equal Opportunity Employer:
IAS is an equal opportunity employer, committed to our diversity and inclusiveness. We will consider all qualified applicants without regard to race, color, nationality, gender, gender identity or expression, sexual orientation, religion, disability or age. We strongly encourage women, people of color, members of the LGBTQIA community, people with disabilities and veterans to apply.
California Applicant Pre-Collection Notice:
We collect personal information (PI) from you in connection with your application for employment or engagement with IAS, including the following categories of PI: identifiers, personal records, commercial information, professional or employment or engagement information, non-public education records, and inferences drawn from your PI. We collect your PI for our purposes, including performing services and operations related to your potential employment or engagement. For additional details or if you have questions, contact us at compliance@integralads.com.
Attention agency/3rd party recruiters: IAS does not accept any unsolicited resumes or candidate profiles. If you are interested in becoming an IAS recruiting partner, please send an email introducing your company to recruitingagencies@integralads.com. We will get back to you if there's interest in a partnership.
Job Description:
Integral Ad Science (IAS) is a global technology and data company that builds verification, optimization, and analytics solutions for the advertising industry, and we’re looking for a Staff Machine Learning Engineer on the Data Science Team. If you are excited by technology that has the power to handle hundreds of thousands of transactions per second; collect tens of billions of events each day; and evaluate thousands of data points in real-time all while responding in just a few milliseconds, then IAS is the place for you!
As a Staff Machine Learning Engineer at IAS, you will be part of a team that is at the center of innovation for the company and a major contributor to our core products. You will oversee a sophisticated suite of data science systems making large-scale business predictions across the open web, social networks, video, and mobile apps. At the Staff level, you are expected to be a technical pillar for the organization. You will take ownership of open, highly ambiguous business problems and translate them into scalable ML architectures. You will define technical roadmaps, set the standard for ML engineering practices, and push the boundaries of applied machine learning to deliver best-in-class solutions for our clients. Innovation is at the heart of our competitive advantage, and you will cultivate it by mentoring talent and raising the technical bar across multiple teams. The types of challenges we solve have attracted people from industry and academia with diverse backgrounds. We’re passionate about maintaining an open and collaborative environment, where team members bring their own unique style of thinking and tools to the table.
What you’ll get to do:
- Technical Leadership & Vision: Drive the architectural vision and system design for our core AI/ML-based services.
- Act as the technical lead for complex, multi-quarter initiatives from inception to global deployment.
- Architect at Scale: Design and build large-scale deep learning infrastructure and platforms for distributed model training, ensuring low-latency and high-availability at enterprise scale.
- Cross-Functional Influence: Partner with Product Management, Core Engineering, and executive stakeholders to align ML capabilities with business strategy.
- Translate abstract product requirements into concrete technical designs.
- Act as a Multiplier: Mentor and guide senior and mid-level data scientists and engineers.
- Establish standard methodologies, define code quality expectations, and lead architecture design reviews.
- Infrastructure Mastery: Work with large-scale AI training infra components (accelerators, network fabrics, CUDA, NCCL, RDMA) and big data ecosystems (Databricks, Spark, Kubernetes, Kafka, Prometheus).
- End-to-End Ownership: Design, develop, and support robust CI/CD pipelines for AI/ML services, ensuring models transition smoothly from research into reliable production endpoints.
You should apply if you have most of this experience:
- PhD/Master’s degree in a technical field such as computer science, mathematics, statistics, or equivalent years of experience.
- 7+ years of machine learning experience in industry, with a proven track record of operating at a Lead, Principal, or Staff level.
- System Design & Architecture: Deep expertise in designing complex machine learning systems, ranking infrastructures, and data pipelines that handle massive throughput.
- ML Frameworks: Extensive, production-hardened experience working with frameworks such as PyTorch, JAX, or TensorFlow.
- Production Coding: Strong, production-grade programming skills in Python, Go, Java, or C++, along with a deep understanding of software design principles and algorithms.
- Ambiguity & Execution: Proven ability to thrive in ambiguity, take large unstructured problems, and independently drive them to successful technical resolutions.
- Mentorship: A strong history of collaborating with, elevating, and mentoring engineering talent.
IAS Pay Transparency:
The annualized base salary ranges for the primary location, and any additional locations are listed below. Our pay ranges are based on the work location. As part of IAS compensation package, we offer a comprehensive benefits package that includes paid time off, health insurance (medical, dental, vision) as well as PPO, HSA and FSA options and 401k with employer matching contributions. All full-time employee roles include competitive compensation and are eligible for an annual bonus and/or other incentive plans. Each candidate’s compensation package is based on multiple factors, but not limited to, geography, experience, skills, job duties, and business need.
Primary Location:
US - New York, NY
Primary Location Base Pay Range:
$135,100.00 - $231,600.00 Annual
Additional Locations:
USA - Remote
Additional Locations Pay Range:
$119,000.00 - $204,000.00 USD Annual
About Integral Ad Science:
Integral Ad Science (IAS) is a leading global media measurement and optimization platform that delivers the industry’s most actionable data to drive superior results for the world’s largest advertisers, publishers, and media platforms. IAS’s software provides comprehensive and enriched data that ensures ads are seen by real people in safe and suitable environments, while improving return on ad spend for advertisers and yield for publishers. Our mission is to be the global benchmark for trust and transparency in digital media quality. For more information, visit integralads.com.
Equal Opportunity Employer:
IAS is an equal opportunity employer, committed to our diversity and inclusiveness. We will consider all qualified applicants without regard to race, color, nationality, gender, gender identity or expression, sexual orientation, religion, disability or age. We strongly encourage women, people of color, members of the LGBTQIA community, people with disabilities and veterans to apply.
California Applicant Pre-Collection Notice:
We collect personal information (PI) from you in connection with your application for employment or engagement with IAS, including the following categories of PI: identifiers, personal records, commercial information, professional or employment or engagement information, non-public education records, and inferences drawn from your PI. We collect your PI for our purposes, including performing services and operations related to your potential employment or engagement. For additional details or if you have questions, contact us at compliance@integralads.com.
Attention agency/3rd party recruiters: IAS does not accept any unsolicited resumes or candidate profiles. If you are interested in becoming an IAS recruiting partner, please send an email introducing your company to recruitingagencies@integralads.com. We will get back to you if there's interest in a partnership.
Machine Learning Jobs by Experience Level
Top Cities Hiring Machine Learnings
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Find Machine Learning JobsMachine Learning Job Market
Who's Hiring
- Apple173
- CVS Health120
- TikTok99
- Google84
- JPMorganChase82
Top Industries Hiring
- Technology & Software135
- Electronics & Hardware55
- Banking & Financial Services22
- Automotive19
- Biotechnology & Pharmaceuticals19
What Employers Look For
The qualifications that appear most often in machine learning jobs.
- Proficiency in Python and at least one major ML framework such as PyTorch or TensorFlow
- Experience designing, training, and deploying machine learning models in production environments
- Strong foundation in statistics, linear algebra, and probability theory
- Familiarity with cloud platforms such as AWS, GCP, or Azure for ML workloads
- Experience with data pipelines, feature engineering, and model evaluation workflows
- Bachelor's or master's degree in computer science, statistics, mathematics, or a related field
Tips for Your Machine Learning Job Search
Tailor your resume to the stack
Machine learning job descriptions vary widely by framework. Swap generic terms like 'deep learning experience' for the exact tools listed, whether that's PyTorch, JAX, or Hugging Face Transformers. Recruiters and automated filters both scan for this match before a human reads your resume.
Showcase model performance with metrics
Hiring managers care about outcomes, not process. Replace 'built a recommendation model' with the actual lift it delivered, such as a reduction in latency or an improvement in click-through rate. Quantified results differentiate you from candidates who describe responsibilities instead of results.
Apply early to roles that fit
Migrate Mate lists machine learning openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target roles by deployment context
A research-heavy role at a tech lab and a production machine learning role at a fintech company need different application angles. Lead with MLOps, CI/CD pipelines, and latency constraints when targeting production environments. Lead with publications and experimentation frameworks when applying to research-oriented teams.
Prepare a systems design answer for ML
Most machine learning interviews include a system design round specific to the role, like designing a fraud detection pipeline or a real-time ranking system. Practice articulating trade-offs between batch and streaming inference, model versioning, and feature store architecture before your first screen.
Negotiate on scope, not just base pay
Machine learning roles often have flexible scope around data ownership, compute budget, and research time. If an offer's compensation is fixed, ask about access to GPU clusters, conference budgets, or the ratio of research to production work. These factors affect your long-term career development as much as salary.
Machine Learning Jobs: Frequently Asked Questions
Which companies are hiring the most machine learnings?
The companies hiring the most machine learnings right now include Apple, CVS Health, and TikTok, with the largest share of openings in California, Washington, and New York, based on current listings on Migrate Mate as of September 2026. Demand is concentrated in technology, financial services, and healthcare sectors.
How many machine learning jobs are remote?
About 62% of machine learning openings are fully remote or hybrid as of September 2026, making it one of the more flexible technical disciplines for location-independent work. Research engineering and NLP roles tend to have the highest remote availability, while applied roles tied to proprietary hardware or on-site data infrastructure are more often in-office.
How do you become a machine learning?
Start by building a strong foundation in Python programming, linear algebra, and probability. Work through core ML concepts using open datasets and document your projects in a public portfolio such as GitHub. Apply for junior or associate roles, internships, or research assistant positions that offer hands-on model development, and continue deepening your knowledge of deployment and MLOps as you gain experience.
Can you get a machine learning job with little or no experience?
Yes, entry-level machine learning roles exist and employers hiring for them prioritize demonstrated project work over years of experience. Build two or three end-to-end projects that show data preprocessing, model training, evaluation, and a basic deployment step. Contributing to open-source ML libraries and writing clearly about your technical decisions online also helps employers assess your skills when your resume is light.
What does the machine learning interview process look like?
Most machine learning interviews include an initial recruiter screen, a technical phone screen covering coding and ML fundamentals, a take-home or live machine learning case study, and a final loop with multiple rounds covering system design, model evaluation, and a cross-functional stakeholder interview. Research-focused roles often add a presentation of past work or a paper review discussion.
Where can I find and apply to machine learning jobs?
You can find and apply to machine learning jobs on Migrate Mate, which lists current openings from employers across the United States. Search the listings to find roles that match your experience and specialization, then apply directly to each one that fits.
See All 2,403+ Machine Learning Jobs
Find roles that match your experience and apply in just a few clicks.
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