• Design and implementation of production AI and agent systems • Development of modern architectures around LLMs, knowledge graphs and data integration • Not only setting up solutions conceptually, but also bringing them hands-on into production • Responsibility for deployment and optimization of on‑prem LLMs (e.g., vLLM, Ollama)

Role Description We are looking for a skilled Machine Learning Engineer / Python Developer to develop and deploy AI-based solutions. This is a Work From Home (Remote) position, allowing you to work from any location. You will be responsible for building machine learning models, developing backend systems, and integrating AI solutions with modern full-stack applications. You will work on real-world AI use cases, collaborating on end-to-end development from data processing and model training to deployment and optimization. Qualifications - 1 to 3 years of experience - Freshers with strong project experience can apply Requirements - GitHub or portfolio is required - Hands-on project experience in AI or ML - Strong problem-solving skills Benefits - Flexible Work From Home / Remote opportunity - Competitive salary based on experience and skills - Opportunity to work on real-world AI and Machine Learning projects - Career growth and learning opportunities in AI technologies - Collaborative and supportive work environment - Exposure to modern tools, frameworks, and cloud technologies - Hands-on experience with scalable AI applications - Performance-based growth opportunities - Work-life balance and flexible working hours - Opportunity to contribute to innovative and impactful projects

Role Description As a Senior Software Engineer, you will help drive the design and development of our agent compute delivery platform centered around our custom agent sandbox cloud VM solution. Your responsibility will be to improve NVIDIA's agent sandbox services into running full agentic use cases that are scalable and secure. You will partner with teams all across NVIDIA to enable their AI workflows. This is a role for someone who wants to build at the frontier of AI, creating the bleeding edge platform for next-gen agentic services. - Leading cloud VM platform initiatives including design, writing code, and performing deployments. - Collaborating with other engineering teams across NVIDIA to drive the execution of meaningful products for the business. - Building automation for our platform. - Help in continuously setting the standard of our code quality and security. Qualifications - Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience). - 8+ years experience in software engineering, with a focus on backend development. - Proven deep cloud architecture experience in AWS or Azure. - Experience in spec-driven development - using agents to multiply your developer productivity. - Proficiency in simple, yet efficient systems design. - Good communications skills with a desire to be a team player. Requirements - Python and Go expertise. - Comprehensive understanding of infrastructure security. Benefits - Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 270,250 USD. - You will also be eligible for equity and benefits. Company Description NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.

• Design, build, and maintain agentic AI pipelines to automate semantic mapping, dimension mining, and ontology-driven reasoning. • Create and evolve enterprise ontologies in RDF/OWL. • Engineer LLM-powered services for schema understanding. • Implement SPARQL querying and reasoning layers over knowledge graphs. • Architect and deliver Python-based microservices and batch pipelines. • Build and optimize dimension and fact generation pipelines on Microsoft Fabric. • Define and enforce engineering standards and reusable components for data platforms. • Partner with data architects, domain SMEs, and governance teams. • Conduct code reviews, mentor engineers, and influence technical decisions.