AI ML Platform Jobs
AI ML Platform jobs are open across technology, finance, healthcare, and defense, from new-grad to staff and principal engineer, with specializations in MLOps, model serving infrastructure, and distributed training pipelines. Find a role that fits from the openings below and apply directly.
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Showing 5 of 70+ AI ML Platform jobs
INTRODUCTION
We are looking for an experienced Windows platform architect to drive AI system performance and power enhancements into the SW and HW stacks and SW tools of state-of-the-art machine learning solutions on Snapdragon platform such that the AI performance and power is delivered to final applications while keeping application developer experience and ease of deployment competitively high. As a senior member of the team responsible for competitive advantages in end-to-end delivery of AI functionality, performance, power on Snapdragon compute platform, you will have opportunity to drive joint HW-SW design and architecture spec while representing requirements of Windows on Snapdragon application developers for multiple AI use-cases and ensure the Snapdragon AI platform, and tools deliver the industry leading performance and power including necessary security requirements. You will also study Enterprise agentic AI workflows, define, and drive implementation of on-device AI platform components such that Snapdragon becomes the preferred choice for Enterprise AI PCs. You will work closely with software and hardware architects, project engineers, product managers, customer engineers, OEMs, OS partners and application developers. Ideal candidate has extensive experience in architecture aware AI Model system performance optimization on Windows PC/Laptop, architecture aware benchmarking, and performance breakdown analysis with GPU, NPU, and knowledge of state of the art in AI for multiple domains such as Computer Vision, Audio, Generative AI, Agentic AI.
ROLE AND RESPONSIBILITIES
Understand trends in ML network design, through customer engagements and latest state of the art, and determine how this will affect both SW and HW design
Analyze bottlenecks in end to end use-cases and application of ML/AI algorithms and workloads on exploratory and existing Qualcomm HW and SW stacks through simulation and on-device characterization
On-device correlation and tuning of algorithm versus pre-silicon predictions
Analyze Enterprise AI workflows for common user personas and propose components that make Snapdragon AI PCs work complimentarily with cloud AI components of the enterprise workflow to deliver measurably increased productivity and user-experience for enterprise users
Interface with other cross-site and cross-functional teams to arrive at best-in-class performant reference implementations, tools, and documentation that are directly leveraged by 3rd party app developers
Analyze, develop, propose new features and designs to system design of next gen SoCs that reduce performance bottlenecks through the workflow
MINIMUM QUALIFICATIONS
* Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 8+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 7+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
SKILLS AND EXPERIENCE
Excellent understanding of AI frameworks (e.g., TensorFlow, PyTorch), GPU/NPU programming, and parallel computing. Experience with large language models/foundational models development and deployment a plus
Good Understanding of complete Software stack and familiarity with AI and other multimedia hardware acceleration technologies
Experience with performance optimization of AI application on Windows using processor specific optimization tools/libraries/primitives on GPU, NPU
Strong background in end to end system performance analysis using profiling tools, and algorithmic modification methods for performance improvement is essential
Knowledge of state of the art in Agentic AI
Knowledge of computer architecture, embedded system implementations
Strong software engineering principles are essential
Proficiency in programming languages such as Python, C++
Excellent communication skills to articulate complex technical concepts to non-technical and technical stakeholders
Strong leadership abilities to motivate and guide development teams
Detail-oriented with strong problem-solving, analytical, and debugging skills with the ability to think strategically and drive innovative solutions
Demonstrated ability to learn, think and adapt in a fast-changing environment
Familiarity with software development methodologies, version control systems, and agile project management practices
15+ years experience in High Performance Computing System Engineering or Software with 5+ years in AI system optimization
* Masters or PhD in Computer Science or Electrical Engineering
EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
PAY RANGE AND OTHER COMPENSATION & BENEFITS
$200,800.00 - $301,200.00
The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at this link. If you would like more information about this role, please contact Qualcomm Careers.
To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
INTRODUCTION
We are looking for an experienced Windows platform architect to drive AI system performance and power enhancements into the SW and HW stacks and SW tools of state-of-the-art machine learning solutions on Snapdragon platform such that the AI performance and power is delivered to final applications while keeping application developer experience and ease of deployment competitively high. As a senior member of the team responsible for competitive advantages in end-to-end delivery of AI functionality, performance, power on Snapdragon compute platform, you will have opportunity to drive joint HW-SW design and architecture spec while representing requirements of Windows on Snapdragon application developers for multiple AI use-cases and ensure the Snapdragon AI platform, and tools deliver the industry leading performance and power including necessary security requirements. You will also study Enterprise agentic AI workflows, define, and drive implementation of on-device AI platform components such that Snapdragon becomes the preferred choice for Enterprise AI PCs. You will work closely with software and hardware architects, project engineers, product managers, customer engineers, OEMs, OS partners and application developers. Ideal candidate has extensive experience in architecture aware AI Model system performance optimization on Windows PC/Laptop, architecture aware benchmarking, and performance breakdown analysis with GPU, NPU, and knowledge of state of the art in AI for multiple domains such as Computer Vision, Audio, Generative AI, Agentic AI.
ROLE AND RESPONSIBILITIES
Understand trends in ML network design, through customer engagements and latest state of the art, and determine how this will affect both SW and HW design
Analyze bottlenecks in end to end use-cases and application of ML/AI algorithms and workloads on exploratory and existing Qualcomm HW and SW stacks through simulation and on-device characterization
On-device correlation and tuning of algorithm versus pre-silicon predictions
Analyze Enterprise AI workflows for common user personas and propose components that make Snapdragon AI PCs work complimentarily with cloud AI components of the enterprise workflow to deliver measurably increased productivity and user-experience for enterprise users
Interface with other cross-site and cross-functional teams to arrive at best-in-class performant reference implementations, tools, and documentation that are directly leveraged by 3rd party app developers
Analyze, develop, propose new features and designs to system design of next gen SoCs that reduce performance bottlenecks through the workflow
MINIMUM QUALIFICATIONS
* Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 8+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 7+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
SKILLS AND EXPERIENCE
Excellent understanding of AI frameworks (e.g., TensorFlow, PyTorch), GPU/NPU programming, and parallel computing. Experience with large language models/foundational models development and deployment a plus
Good Understanding of complete Software stack and familiarity with AI and other multimedia hardware acceleration technologies
Experience with performance optimization of AI application on Windows using processor specific optimization tools/libraries/primitives on GPU, NPU
Strong background in end to end system performance analysis using profiling tools, and algorithmic modification methods for performance improvement is essential
Knowledge of state of the art in Agentic AI
Knowledge of computer architecture, embedded system implementations
Strong software engineering principles are essential
Proficiency in programming languages such as Python, C++
Excellent communication skills to articulate complex technical concepts to non-technical and technical stakeholders
Strong leadership abilities to motivate and guide development teams
Detail-oriented with strong problem-solving, analytical, and debugging skills with the ability to think strategically and drive innovative solutions
Demonstrated ability to learn, think and adapt in a fast-changing environment
Familiarity with software development methodologies, version control systems, and agile project management practices
15+ years experience in High Performance Computing System Engineering or Software with 5+ years in AI system optimization
* Masters or PhD in Computer Science or Electrical Engineering
EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
PAY RANGE AND OTHER COMPENSATION & BENEFITS
$200,800.00 - $301,200.00
The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at this link. If you would like more information about this role, please contact Qualcomm Careers.
To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
See All 70+ AI ML Platform Jobs
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Find AI ML Platform JobsAI ML Platform Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Apple6
- NVIDIA3
- CrowdStrike2
- Databricks2
- Honeywell2
Top Industries Hiring
- Technology & Software37
- Electronics & Hardware12
- Consulting & Professional Services8
- Banking & Financial Services5
- Artificial Intelligence3
What Employers Look For
The qualifications that appear most often in AI ML platform jobs.
- Proficiency in Python and experience building or maintaining ML pipelines at scale
- Hands-on experience with containerization and orchestration tools such as Docker and Kubernetes
- Familiarity with at least one managed ML platform such as SageMaker, Vertex AI, or Azure ML
- Experience designing or operating distributed training and model serving infrastructure
- Understanding of CI/CD principles applied to model training, evaluation, and deployment workflows
- Bachelor's or master's degree in computer science, engineering, or a closely related quantitative field
Tips for Your AI ML Platform Job Search
Quantify your infrastructure impact clearly
Hiring managers want to see throughput, latency, or cost numbers tied to work you shipped. Replace vague descriptions like 'improved model deployment' with concrete outcomes such as reduced pipeline runtime or cut cloud spend on inference workloads.
Separate MLOps from software engineering roles
AI ML platform openings split into infrastructure-heavy and research-adjacent tracks. Read job descriptions carefully for keywords like Kubeflow, Ray, or Triton versus SageMaker or Vertex AI to apply to roles that actually match your stack and experience level.
Apply early to roles that fit
Migrate Mate lists ai ml platform openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Build a public artifact before your system design round
AI ML platform interviews almost always include a system design exercise. Pushing a reproducible training pipeline or a feature store prototype to GitHub before you interview gives you a real example to reference when describing architectural trade-offs.
Tailor your cover letter to the orchestration stack
Most teams list their orchestration tools in the job description. Mentioning Airflow, Prefect, or Argo Workflows by name, with context on how you used them, signals you'll ramp faster than candidates who write generic platform experience statements.
Negotiate scope alongside compensation
In AI ML platform roles, ownership of the platform roadmap varies widely between companies. Ask during the offer stage which components the team controls end-to-end versus which are handed off to data science or DevOps, so you know the actual scope before accepting.
AI ML Platform Jobs: Frequently Asked Questions
Which companies are hiring the most ai ml platforms?
The companies hiring the most ai ml platforms right now include Apple, NVIDIA, and CrowdStrike, with the largest share of openings in California, New York, and Washington, based on current listings on Migrate Mate as of June 2026. Demand is concentrated in companies scaling inference infrastructure or moving model development from research into production.
How many ai ml platform jobs are remote?
About 40% of ai ml platform openings are fully remote or hybrid as of June 2026, reflecting strong demand for distributed engineering talent. Model serving, pipeline observability, and feature engineering sub-roles tend to be the most remote-friendly, while roles involving on-premise GPU cluster management are more likely to require on-site presence.
How do you become a ai ml platform?
Start by building a solid foundation in Python, distributed systems, and at least one cloud provider. Work on end-to-end ML pipeline projects, even personal ones, to develop hands-on experience with orchestration, versioning, and model deployment. Contributing to open-source MLOps tools strengthens your portfolio. Moving into the role often means transitioning from a software engineering or data engineering background while picking up ML-specific tooling on the job.
Can you get an ai ml platform job with little experience?
Yes, entry-level ai ml platform roles exist, particularly at companies building out their platforms for the first time. Focus on demonstrating working knowledge of a pipeline orchestration tool, containerization basics, and a completed end-to-end project. Applying to smaller companies or startups where the platform team is early-stage gives you a better chance of being evaluated on potential rather than years of experience.
What does the ai ml platform interview process look like?
Most ai ml platform interviews include a recruiter screen, a technical phone interview covering Python and systems fundamentals, and an on-site or virtual loop with a machine learning system design round, a coding exercise focused on data structures or distributed concepts, and a cross-functional interview with data scientists or product managers. Some companies also include a take-home that asks you to design or debug a pipeline component.
Where can I find and apply to ai ml platform jobs?
You can find and apply to ai ml platform jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your experience and specialization, then apply directly to each one that fits. New openings are added regularly, so checking back frequently gives you access to roles as soon as they're posted.
See All 70+ AI ML Platform Jobs
Jump back to the full list of openings and apply to any AI ML platform role that fits.
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