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Software Engineer Internal Systems Salary India Jobs

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Explore current software engineer internal systems salary india jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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Baseten
📍 San Francisco• Full-time
1mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Are you passionate about advancing the application of artificial intelligence? We are looking for a Software Engineer focused on ML performance to join our dynamic team. This role is ideal for someone who thrives in a fast-paced startup environment and is eager to make significant contributions to the exciting field of LLM Inference. If you are a backend engineer who thrives on making things faster and is excited about open-source ML models, we look forward to your application. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Model Performance team: Baseten Embeddings Inference: The fastest embeddings solution available The Baseten Inference Stack Driving model performance optimization RESPONSIBILITIES Implement, refine, and productionize cutting-edge techniques (quantization, speculative decoding, kv cache reuse, chunked prefill and LoRA) for ML model inference and infrastructure. Deep dive into underlying codebases of TensorRT, PyTorch, TensorRT-LLM, vllm, sglang, CUDA, and other libraries to debug ML performance issues. Apply and scale optimization techniques across a wide range of ML models, particularly large language models. Collaborate with a diverse team to design and implement innovative solutions. Own projects from idea to production. REQUIREMENTS Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or related field. Experience with one

pythondockerkubernetes
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Render
📍 United States• Full-time
1mo ago

At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 6.5 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $257M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. Applying to Render We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, an

restaigo
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B
Baseten
📍 San Francisco• Full-time
1mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE We’re seeking a GPU Kernel Engineer to join our team at the cutting edge of AI acceleration, where your code directly impacts the performance of state-of-the-art machine learning models. As a GPU Kernel Engineer, you'll craft the foundation that powers modern AI workloads, optimizing every microsecond of computation to enable breakthrough applications. You'll work in a fast-paced, intellectually stimulating environment where technical excellence is paramount and your contributions directly influence production systems serving millions of users across numerous products. This role offers exceptional growth potential for engineers passionate about low-level optimization and high-impact systems work. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Model Performance team: Baseten Embeddings Inference: The fastest embeddings solution available The Baseten Inference Stack Driving model performance optimization RESPONSIBILITIES Core Engineering Responsibilities Design and implement high-performance GPU kernels for key ML operations, including matrix multiplications, attention mechanisms, and mixture-of-experts routing Write and optimize code using CUDA, PTX assembly, and architecture-specific techniques Apply advanced performance optimization methods such as memory coalescing, warp-level programming, tensor core acceleration, and compute/memory overlap Performance & Innovation Impl

awsmachine learningai
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B
1mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten is building its own GPU infrastructure for large-scale inference. As we move into large scale, high-density NVIDIA systems, the hardest failures are intermittent, cross-layer, and difficult to prove: RoCE congestion, InfiniBand stalls, ECN/DCQCN mis-tuning, bad optics, RNIC issues, host kernel stalls, GPU driver problems, and workload symptoms that look like network problems, but are not. We are hiring a Lead Software Engineer to build a first-class observability and root-cause analysis system for GPU fabrics. This is a hard distributed systems problem, not a dashboarding problem. The system will collect high-volume signals from switches, hosts, active probes, and inference services; reduce and correlate them in real time; understand topology and service ownership; and produce actionable diagnosis while an incident is still unfolding. This role sits at the boundary between networking and inference software. RDMA data paths, GPUDirect transfers, prefill/decode disaggregation, KV cache movement, request routing, and workload backpressure can all create fabric symptoms or hide real fabric failures. The goal is to tell an operator, quickly and with evidence, whether an incident is caused by the fabric, host, NIC, GPU, RDMA path, scheduler, or serving layer — and what to do next. EXAMPLE INITIATIVES Real-time telemetry engine — Build the ingestion, reduction, storage, and query path for high-cardinality fab

kubernetesmachine learningai
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B
1mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE: Voice is becoming the internet’s next interface, but a production-grade Voice AI system is "hard to build" . You’ll join a small founding team of Baseten Voice AI, focused on bringing state-of-the-art open source models into production for Voice AI customers across productivity, customer service, clinical conversation, creator tools, education, and more. You’ll make a meaningful impact on people’s daily lives and help reshape these industries. This is a high-impact, high-ownership role. You will be the primary owner of Baseten Voice AI - our in-house inference stack to power Voice AI models - from product roadmap through engineering implementation. You’ll partner closely with Forward Deployed Engineers, Model Performance Engineers, and sister engineering teams to push the boundaries of Voice AI. EXAMPLE INITIATIVES: Develop world-class model serving stack for state-of-the-art open-source voice models - reduce end-to-end and tail latency (p95/p99), increase throughput, and improve GPU efficiency via profiling, runtime tuning, and server-level optimizations. Build large-scale, real-time infrastructure for multi-model voice agents - orchestrate STT, TTS, and agent components with streaming I/O to meet customer SLOs. Design tight training and inference iteration loops for voice model customization - enable fast evaluation, safe rollout, and rapid experimentation for custom voice model development. Past projects:

pythondockerkubernetes
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B
1mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten’s Inference Stack team builds the distributed runtime that powers large-scale LLM inference across our platform. We operate at the intersection of distributed systems, model performance, infrastructure, and developer experience. We enable customers to deploy and operate cutting-edge LLM models with industry-leading performance, scalability, reliability, and ease of use. As a Software Engineer on the Inference Stack team, you’ll work across the stack - from the developer experience customers use to deploy models, the libraries used for features like tool calling and reasoning, all the way down to the systems we use to orchestrate deployments in Kubernetes and route traffic efficiently. This is an ideal role for engineers who enjoy owning systems in production, solving hard integration problems, and making complex infrastructure simple and reliable for users. EXAMPLE INITIATIVES Blog Posts https://www.baseten.co/blog/nvidia-dynamo-day-baseten-inference-stack/ https://www.baseten.co/blog/how-baseten-achieved-2x-faster-inference-with-nvidia-dynamo/ https://www.baseten.co/blog/how-baseten-multi-cloud-capacity-management-mcm-powers-cloud-self-hosted-and-hybr/#comparing-deployment-options-cloud-vs-self-hosted-vs-hybrid RESPONSIBILITIES Develop infrastructure and orchestration systems for deploying and managing large-scale distributed LLM inference Work across the stack, from customer-facing features to low-le

kubernetesci/cdrest
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R
Render
📍 United States• Full-time
1mo ago

At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 6.5 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $257M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. Applying to Render We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, an

typescriptreactkubernetes
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B
Baseten
📍 San Francisco• Full-time
1mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE We’re looking for a customer-obsessed software engineer to come ship with us. You’ll own features like multi-node training and products like serverless reinforcement learning (RL) from conception to MVP (and from MVP to GA!). You’ll work through the stack, architecting solutions from API and UI down to our infrastructure layer. You’ll fine tune models yourself to develop an understanding of user workflows. You’ll work closely with research engineers leveraging state-of-the-art training techniques to build experiences that accelerate model development and solve for real pain points. If you’re excited to dive deep into the training, let’s talk! THE PRODUCT Take a look at what we’ve built so far: Overview of the product so far Training docs overview Story of the Training product Research we've done EXAMPLE INITIATIVES Checkpointing Pipeline: Our checkpointing pipeline starts with automated checkpointing, a feature that ensures that versions of models created during training are automatically backed up to the cloud. Users are able to then deploy checkpoints seamlessly into inference servers, providing point-and-click integrations into inference frameworks like vLLM and Baseten’s Inference Stack. This enables customers to quickly evaluate the performance of their checkpoints with real traffic. Multinode training: Multinode training enables customers to easily run training jobs across multiple compute nodes, enablin

kubernetesrestmachine learning
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ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. At Baseten, we are building the global operating system for distributed, heterogeneous AI hardware. We believe that as LLM and multi-modal workloads scale, the network is the computer. We are looking for foundational engineers to lead our GPU Networking efforts, making RDMA a first-class building block in our infrastructure and unlocking the next generation of distributed inference optimizations. THE OPPORTUNITY Networking and compute are no longer separate disciplines; they are converging. The massive throughput of H100, B200, and NVL72 architectures enables and demands a new approach where communication is co-optimized alongside computation. We are entering an era where the network is an active accelerator, leveraging smart hardware offloads and direct interconnects to ensure that data movement operates at wire-speed. In this role, you will go beyond network configuration to architect the software fabric that unifies thousands of GPUs into a cohesive operating system. While you will leverage the best of the open-source ecosystem, you won't be limited by it. Where off-the-shelf solutions stop, you will build from scratch, engineering the primitives required to co-optimize communication and compute for Disaggregated Serving, Wide Expert Parallelism (WideEP), and lightening cold starts. WHAT YOU'LL DO Make RDMA First-Class: You will work on integrating RDMA/RoCE/InfiniBand capabilities directly into our inference stack,

pythonkubernetesmachine learning
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B
Baseten
📍 San Francisco• Full-time
1mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE The largest, most demanding enterprises are starting to run on Baseten, and they arrive with a range of security, compliance, and procurement requirements. As a Senior Engineer on Baseten's enterprise engineering team, you'll build the capabilities that enable large organizations like Writer, HubSpot, and Notion to succeed on Baseten. Enterprise engineering authors the core building blocks, APIs, and user experiences powering the Baseten platform: identity and access management, billing, regional isolation, and self-hosted and single-tenant deployment options. This is deep product and systems work across the full stack, from designing authentication and authorization systems using standards like OAuth and OIDC to shipping the admin experiences enterprise IT teams use to manage their organization. EXAMPLE INITIATIVES Recent and upcoming work on the team: Fine-grained authorization for users, service accounts, and agentic workloads SSO and SCIM support, allowing customers to centralize and automate access to Baseten Expanding the billing platform to support evolving pricing models, advanced data exports, and controls to manage spend In-product management and enforcement of customer compliance requirements like data residency and HIPAA Securing network paths in and out of a customer's models with private connectivity and ingress and egress restrictions Allowing customers to run Baseten inside their own VPC, on-pr

kubernetesrestmachine learning
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B
1mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As a Software Engineer at on the Training Infrastructure team, you'll architect and lead development of our training platform, supporting top tier research engineers and model developers. You'll make key technical decisions for the infrastructure enabling developers to deploy, scale, and monitor their workloads with high performance and reliability. You’ll own scheduling, storage, networking, reliability, and observability of technical systems in the training stack EXAMPLE INITIATIVES Take a look at what we’ve built so far: Overview of the product so far Training docs overview Story of the Training product Research we've done RESPONSIBILITIES Design and architect scalable infrastructure systems for our ML training platform (e.g. scheduling, storage, and networking) Partner closely with developers and research engineers to translate complex training requirements into technical solutions Design and architect a global training scheduler Design and architect reinforcement learning systems and continuous learning pipelines Drive long-term improvements to improve reliability of systems and velocity of development Partner closely with SRE and Capacity teams to unlock state of the art training infrastructure Make critical architectural decisions balancing performance with system reliability Lead technical discussions and mentor junior engineers on infrastructure best practices Contribute to long-term technical strateg

pythonawsgcp
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A
1mo ago

About Anyscale: At Anyscale, we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We're commercializing Ray, a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI, Uber, Spotify, Instacart, Cruise, and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we're building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role Anyscale is looking for a Software Engineer to join the Platform and Infrastructure team. Anyscale aims to provide the next generation of tools and infrastructure to make developing and running distributed AI applications in the cloud as easy as on your laptop. As part of the team, we build the scalable, secure, and robust backbone that enables this vision, ensuring that our "infinite laptop" vision scales to meet the most demanding distributed AI workloads in the world. Our team is responsible for both the control plane, which orchestrates cluster management, scheduling, and user access, and the data plane, which ensures high-performance execution of distributed workloads. We are seeking a talented Software Engineer with a strong background in control plane and data plane development, along with expertise in Kubernetes, container orchestration, and cloud-native infrastructure. You will play a crucial role in designing, implementing, and optimizing the critical infrastructure that powers Anyscale's cloud platform. You will have the opportunity to work on open-source Ray, contribute to our infinite laptop proprietary product, and develop seamless integration between the two, while also delivering high-impa

pythonawsazure
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