AI Software Developer Jobs
AI Software Developer jobs are open across technology, finance, healthcare, and defense, from entry-level to principal and staff engineer, with specializations in machine learning engineering, large language model development, and MLOps. Find a role that fits from the openings below and apply directly.
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Whether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward. Join us and, together, we’ll advance your career.
Key Responsibilities
- Select and optimize AI models for autonomous applications, ensuring scalability, low latency, and real-time performance across edge and cloud deployments.
- Collaborate with cross-functional teams to ensure seamless integration of AI frameworks into software stacks, optimizing inference pipelines and model performance for real-world use cases.
- Provide technical leadership and guidance in AI software best practices, focusing on deep learning frameworks, GPU-accelerated computing, model compression, and efficient deployment strategies for autonomous systems.
- Analyze and optimize AI software stack performance, particularly in real-time inference, GPU-accelerated, and autonomous navigation environments, identifying bottlenecks and implementing targeted improvements.
- Stay updated with the latest trends and technologies in AI frameworks, foundation models, edge AI deployment and autonomous systems integration, offering insights and recommendations to continuously advance AI capabilities.
- AI Frameworks: Proven experience designing and implementing solutions using leading AI frameworks such as PyTorch, TensorFlow, JAX, or ONNX Runtime, with a focus on autonomous applications.
- AI Model Analysis & Optimization: Strong knowledge and hands-on experience with model profiling, benchmarking, quantization, pruning, and distillation techniques to optimize AI models for performance and efficiency.
- ROCm, CUDA & GPU Computing: Deep expertise in ROCm or CUDA programming, GPU kernel optimization, and GPU memory management for accelerating AI inference and training workloads.
- System Performance Analysis: Expertise in profiling and analyzing end-to-end AI system performance using tools such as NVIDIA Nsight, TensorRT, Triton Inference Server, or similar profiling and optimization platforms.
- Autonomous Systems: Experience deploying AI models within software stacks, including integration with ROS/ROS2, real-time systems, and edge AI hardware platforms (NVIDIA Jetson, etc.).
- Problem-Solving Skills: Excellent problem-solving skills and attention to detail in debugging complex AI model behavior, performance regressions, and hardware-software interactions.
- Collaboration and Communication: Ability to work collaboratively in a cross-functional team environment with strong written and verbal communication skills.
- Bachelor’s or Master’s in Electrical Engineer, Computer Engineering, Computer Science, or a closely related field
Location
- San Jose or Austin
#LI-BW2
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
Whether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward. Join us and, together, we’ll advance your career.
Key Responsibilities
- Select and optimize AI models for autonomous applications, ensuring scalability, low latency, and real-time performance across edge and cloud deployments.
- Collaborate with cross-functional teams to ensure seamless integration of AI frameworks into software stacks, optimizing inference pipelines and model performance for real-world use cases.
- Provide technical leadership and guidance in AI software best practices, focusing on deep learning frameworks, GPU-accelerated computing, model compression, and efficient deployment strategies for autonomous systems.
- Analyze and optimize AI software stack performance, particularly in real-time inference, GPU-accelerated, and autonomous navigation environments, identifying bottlenecks and implementing targeted improvements.
- Stay updated with the latest trends and technologies in AI frameworks, foundation models, edge AI deployment and autonomous systems integration, offering insights and recommendations to continuously advance AI capabilities.
- AI Frameworks: Proven experience designing and implementing solutions using leading AI frameworks such as PyTorch, TensorFlow, JAX, or ONNX Runtime, with a focus on autonomous applications.
- AI Model Analysis & Optimization: Strong knowledge and hands-on experience with model profiling, benchmarking, quantization, pruning, and distillation techniques to optimize AI models for performance and efficiency.
- ROCm, CUDA & GPU Computing: Deep expertise in ROCm or CUDA programming, GPU kernel optimization, and GPU memory management for accelerating AI inference and training workloads.
- System Performance Analysis: Expertise in profiling and analyzing end-to-end AI system performance using tools such as NVIDIA Nsight, TensorRT, Triton Inference Server, or similar profiling and optimization platforms.
- Autonomous Systems: Experience deploying AI models within software stacks, including integration with ROS/ROS2, real-time systems, and edge AI hardware platforms (NVIDIA Jetson, etc.).
- Problem-Solving Skills: Excellent problem-solving skills and attention to detail in debugging complex AI model behavior, performance regressions, and hardware-software interactions.
- Collaboration and Communication: Ability to work collaboratively in a cross-functional team environment with strong written and verbal communication skills.
- Bachelor’s or Master’s in Electrical Engineer, Computer Engineering, Computer Science, or a closely related field
Location
- San Jose or Austin
#LI-BW2
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
AI Software Developer Jobs by Experience Level
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Who's Hiring
- Google72
- JPMorganChase68
- Amazon44
- Amazon Web Services29
- Apple26
Top Industries Hiring
- Technology & Software46
- Electronics & Hardware13
- Banking & Financial Services10
- Manufacturing7
- Education5
What Employers Look For
The qualifications that appear most often in AI software developer jobs.
- Proficiency in Python and at least one deep learning framework such as PyTorch or TensorFlow
- Experience training, fine-tuning, or deploying large language models or neural networks
- Familiarity with MLOps tools and workflows including model versioning, monitoring, and CI/CD pipelines
- Strong foundation in linear algebra, probability, statistics, and algorithm design
- Bachelor's or master's degree in computer science, machine learning, or a related engineering field
- Experience with cloud platforms such as AWS, GCP, or Azure for model training and inference at scale
Tips for Your AI Software Developer Job Search
Tailor your resume for model ownership
Hiring managers want to see models you built end-to-end, not just ones you consumed. List the problem, the architecture you chose, how you evaluated it, and what happened in production. Generic ML bullet points get filtered out fast.
Show your work in a public repo
For AI roles, a GitHub or Hugging Face profile with documented projects carries more weight than certifications alone. Include experiment logs, model cards, and README files that explain your design decisions, not just the code itself.
Apply early to roles that fit
Migrate Mate lists ai software developer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter openings by the model stack
Job descriptions that list PyTorch versus TensorFlow, or fine-tuning versus pretraining, signal very different day-to-day work. Match your search to the frameworks you know deeply rather than applying broadly and explaining gaps in interviews.
Prepare for a system design round focused on inference
Many AI software developer interviews include a round where you design a serving pipeline, latency budget, or retraining loop. Practice explaining trade-offs between batch and real-time inference and how you would handle model drift at scale.
Negotiate around compute access, not just title
When evaluating an offer, ask specifically about GPU allocation, access to proprietary datasets, and whether models are deployed internally or externally. These factors shape what you can build and what your next role will look like.
AI Software Developer Jobs: Frequently Asked Questions
Which companies are hiring the most ai software developers?
The companies hiring the most ai software developers right now include Google, JPMorganChase, and Amazon, with the largest share of openings in California, Washington, and Texas, based on current listings on Migrate Mate as of September 2026. Demand is spread across both large tech companies and well-funded AI startups.
How many ai software developer jobs are remote?
About 75% of ai software developer openings are fully remote or hybrid as of September 2026, making it one of the more flexible engineering roles available. Positions focused on model research, fine-tuning, and API development tend to be the most remote-friendly, while roles requiring on-site GPU clusters or hardware integration are more likely to require in-person work.
How do you become an ai software developer?
Start by building a strong foundation in Python, linear algebra, and probability. Then work through hands-on projects involving model training and evaluation, using open-source frameworks like PyTorch. Contribute to public repositories, document your experiments clearly, and progress toward roles where you own a model or pipeline end-to-end rather than only consuming existing APIs.
Can you get hired as an ai software developer with little or no experience?
Yes, entry-level ai software developer roles exist, but they expect demonstrated hands-on work even without professional history. Build and publish two or three focused projects that show you can train, evaluate, and deploy a model. Open-source contributions, Kaggle competition write-ups, and well-documented GitHub repositories are treated as proxies for experience by many hiring teams.
What does the ai software developer interview process look like?
The process typically includes a recruiter screen, a technical phone interview covering Python and ML fundamentals, a take-home or live coding round focused on model implementation or data pipelines, and a system design round where you architect an end-to-end ML system. Some companies add a research presentation or a deep dive into a past project you built.
Where can I find and apply to ai software developer jobs?
You can find and apply to ai software developer jobs on Migrate Mate, which lists current openings from across the United States. Find roles that match your background and apply directly to each listing on the platform.
See All 1,304+ AI Software Developer Jobs
Find roles that match your experience and apply in just a few clicks.
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