Architect, deploy, and scale local inference engines, real‑time voice and avatar agents, and complex agentic workflows for a smart‑home and AI‑driven living environment.
Compensation
Competitive Tax-Free Salary: A market-leading monthly package in AED, commensurate with experience.
Responsibilities
Deploy, tune, and maintain self‑hosted LLM setups using LMStudio, Exo, vLLM, and Ollama
Design and wire up autonomous AI agents using OpenClaw, Hermes, and custom agentic graphs
Integrate local AI voice agents and agentic control layers directly into Home Assistant
Build resilient middleware that routes queries dynamically between local models and frontier APIs
Provision, manage, and optimize enterprise compute nodes using Linux and Proxmox VE
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Locations (4)
McLean, Virginia, United States
Cambridge, Massachusetts, United States
New York, New York, United States
San Jose, California, United States
Compensation
Cambridge, MA: $197,300 - $225,100 for AI Engineer 4
McLean, VA: $197,300 - $225,100 for AI Engineer 4
New York, NY: $215,200 - $245,600 for AI Engineer 4
San Jose, CA: $215,200 - $245,600 for AI Engineer 4
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Lead the development of LLM inference infrastructure and architectural direction of large-scale ML training and real-time inference systems for Amazon Ads.
Locations (3)
Seattle, Washington, United States
Arlington, Virginia, United States
New York, New York, United States
Compensation
USA, CA, Palo Alto - 193,300.00 - 261,500.00 USD annually
Responsibilities
Lead the development of LLM inference infrastructure for next-generation GenAI workloads at Amazon Ads scale
Own the architectural direction of large-scale ML training and real-time inference systems
Partner with applied scientists to design and optimize end-to-end ML pipelines
Influence technical direction beyond your team by establishing ML infrastructure best practices
Software Engineering Intern - Waterloo University - Winter Session
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Help make the latest AI models run well on our silicon by focusing on LLM inference, numerical optimization, and building agentic workflows for model implementation.
Locations (4)
Sunnyvale, California, United States
Munich, Bavaria, Germany
North America, United States
Europe
Responsibilities
Build agentic workflows to give agents tools to inspect models, change implementations and numerical settings, run emulation and hardware experiments, and diagnose failures.
Bring up new models quickly and work with engineers across the stack to take architectures from reference code to performant execution.
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Locations (4)
Cambridge, Massachusetts, United States
McLean, Virginia, United States
New York, New York, United States
San Jose, California, United States
Compensation
Cambridge, MA: $197,300 - $225,100 for AI Engineer 4
McLean, VA: $197,300 - $225,100 for AI Engineer 4
New York, NY: $215,200 - $245,600 for AI Engineer 4
San Jose, CA: $215,200 - $245,600 for AI Engineer 4
Responsibilities
Senior Applied Scientist, Sponsored Products and Brands
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave.
Responsibilities
Develop scalable and effective machine learning models and optimization strategies to solve business problems.
Conduct research on new machine learning modeling to optimize all aspects of Sponsored Products business.
Partner with cross-functional teams to deliver AI-powered products
Design, develop, test, deploy, and support AI software components
Invent and introduce state-of-the-art foundation model optimization techniques
Contribute to technical vision and long-term roadmap
Own end-to-end architecture for complex AI systems
Requirements
Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Responsibilities
Partner with cross-functional team to deliver AI-powered products
Design, develop, test, deploy, and support AI software components
Leverage Open Source and SaaS AI technologies
Invent and introduce state-of-the-art foundation model optimization techniques
Contribute to technical vision and long-term roadmap
Requirements
Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
Nice to have: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy
Nice to have: 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms
Nice to have: Experience designing, developing, delivering, and supporting complex AI systems
health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
Cambridge, MA: $197,300 - $225,100 for AI Engineer 4
McLean, VA: $197,300 - $225,100 for AI Engineer 4
New York, NY: $215,200 - $245,600 for AI Engineer 4
San Francisco, CA: $215,200 - $245,600 for AI Engineer 4
San Jose, CA: $215,200 - $245,600 for AI Engineer 4
Responsibilities
Partner with cross-functional teams to deliver AI-powered products
Design and develop AI software components
Leverage Open Source and SaaS AI technologies
Invent foundation model optimization techniques
Contribute to technical vision and roadmap
Requirements
Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
Nice to have: Leadership in AI system development
Nice to have: Experience with cost, latency, throughput tradeoffs
Nice to have: Experience deploying scalable AI solutions on cloud platforms
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