#Machine Learning Engineer - Generative AI
$114,500 - $171,700 USD yearly
Originally posted 8 October 2026 by the employer.
Join our Core Enterprise AI team focused on Agentic AI.
About the role
This role involves designing, developing, and deploying AI systems powered by Large Language Models (LLMs), Agentic AI, Hybrid AI architectures, Retrieval-Augmented Generation (RAG), and autonomous intelligent agents. The focus is on building enterprise-grade AI solutions capable of reasoning, planning, tool usage, workflow orchestration, and autonomous task execution.
What you'll do
- Design and implement Agentic AI systems capable of autonomous reasoning, planning, tool usage, and multi-step execution.
- Build and optimize RAG, Hybrid AI, and knowledge-grounded architectures that augment LLMs with enterprise data, external tools, and domain-specific context.
- Develop and advance self-improving AI agents leveraging feedback loops, reflection, reinforcement learning techniques, automated evaluations, memory systems, and continuous learning frameworks.
- Research, develop, and apply LLM post-training techniques, including supervised fine-tuning (SFT), preference optimization, reinforcement learning, distillation, and domain adaptation.
- Create robust evaluation, benchmarking, observability, and safety frameworks for measuring agent quality, reliability, efficiency, and business impact.
- Build and maintain multi-agent systems and orchestration frameworks that enable collaborative agent workflows and intelligent task automation.
What you'll need
- Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field.
- Strong programming skills in Python.
- Experience with ML frameworks (PyTorch, TensorFlow).
- Practical experience with LLM deployments and fine-tuning.
- Experience with vector databases and embedding models.
- Familiarity with modern AI/ML infrastructure and cloud platforms (AWS, GCP, Azure).
- Strong understanding of RAG architectures and implementation.
Nice to have
- Experience with popular LLM frameworks (Langchain, LlamaIndex, Transformers).
- Knowledge of prompt engineering and chain-of-thought techniques.
- Experience with containerization and microservices architecture.
- Background in Reinforcement Learning.
- Contributions to open-source AI projects.
- Experience with ML ops and model deployment pipelines.
Skills: Agentic AI systems, LLMs, RAG, Hybrid AI, Python, ML frameworks
This role has been open 0 days — well below the 50-day median for Software Engineering Semiconductor roles.
Software Engineering Semiconductor · AI ML Hardware
|
Open roles in category
163
|
Median days open
50 d
|
Median salary
$191k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Qualcomm | All employers we track in this specialty (163 roles · 43 employers) |
|---|---|---|
| Open roles in this specialty | 24 | 163 |
| Open roles in the wider Software, Firmware & Systems family | 733 | 6085 · 146 employers |
| Median days open | 183 d | 50 d (+133 d vs this employer) |
| Median salary (USD postings) | — | $191k |
Skills observed across this category: Agentic AI systems, LLMs, RAG, Hybrid AI, Python, ML frameworks
Who's hiring in this category
- Micron Technology · 28 open roles · median 28 d
- NVIDIA · 24 open roles · median 195 d
- Qualcomm (this employer) · 24 open roles · median 183 d
- Infineon Technologies · 10 open roles · median 37 d
- AMD · 9 open roles · median 72 d
- Applied Materials · 4 open roles · median 79 d
How we counted: 163 open Software Engineering Semiconductor (AI ML Hardware) roles from 43 employers tracked in the SemiconductorJobs index, counted 9 Oct 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.