Jobs in India

Eng in India

2,525 active opportunities ยท Updated October 2026

Explore current eng jobs across India. Filter by work mode, employment type, experience, department, date posted and distance.

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๐Ÿ“ Indiaยท Full-time
โœ“ Quality checked

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. Weโ€™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, weโ€™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 seeking a Staff Software Engineer to lead the technical vision for our Infrastructure team. As a Staff Engineer, you will be responsible for the architectural evolution of our control plane and data plane, ensuring that our "infinite laptop" vision scales to meet the most demanding distributed AI workloads in the world. You will act as a force multiplier, setting the standards for Kubernetes-based cloud-native infrastructure while mentoring engineers and driving cross-functional alignment across the Ray open-source community and our proprietary product teams. Key Responsibilities Architectural Leadership: Define and drive the multi-year technical roadmap for services that orchestrate Ray clusters across diverse cloud and on-premises environments. Systemic Optimization: Lead the design and optimization of high-performance control plane components specifically tailored for large-scale, heterogeneous AI/ML workloads. Platform Reliability: Establish the organization-wide standards for the reliability, scalability, and observability of Anyscale-managed infrastructure. Strategic Integration: Direct the long-term strategy for accelerator integration (GPUs, TPUs) and container management to ens

PythonAWSAzureGCP
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๐Ÿ“ Indiaยท Full-time
โœ“ Quality checkedCompany trend -100%

Synthesia is the worldโ€™s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. What you'll do at Synthesia As a Research Engineer you will join a team of 40+ Researchers and Engineers within the R&D Department working on cutting-edge challenges in the Generative AI space, with a focus on creating high-quality, expressive and real-time synthetic voices. Within the team youโ€™ll have the opportunity to work on the applied side of our research efforts and directly impact our solutions that are used worldwide by over 60,000 businesses. If you are an expert in ML, LLMs, speech generation, conversational models , this is your chance to make a global impact. You will join our Audio Post-Training Team , which works on generative speech and voice synthesis , ensuring our in-house voice models reach production-level quality, speed, and robustness. Typical projects include: Develop and evaluate streaming and speech-to-speech systems, enabling low-latency, interactive voice synthesis. Adapt models for new conditioning inputs (emotion, speed, prosody, speaker control, etc.). Implement post-training optimization techniques (quantization, pruning, distillation) to improve efficiency and latency in real-time speech generation. Integrate and test novel architectures, such as neural codecs, diffusion, or

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