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Senior Ai Enabled Full Stack Developer Experienced Jobs

7,101 active opportunities Β· Updated for October 2026

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Explore current senior ai enabled full stack developer experienced jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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1mo ago

About the Role Anyscale is seeking a Senior / Staff Product Manager to lead Ray Data, our scalable data processing library for ML and AI workloads. This is a uniquely challenging role that requires balancing open source growth with commercial differentiation - driving rapid adoption in the open source Ray Data ecosystem while building compelling proprietary features for Anyscale RunTime, our high-performance commercial engine. You'll own the entire Ray Data product roadmap in a competitive landscape, working closely with the engineering team, the field team, enterprise customers, and the open source community. Success requires: Deeply ingraining yourself into the end-user experience to understand the nature of the product and its gaps and tradeoffs Working closely with customers and open source users to draw the subtle line between growth and commercialization Strategic thinking about which parts of the ML/Data lifecycle to focus on, identifying opportunities where our architectural strengths create the most value. Thinking deeply about and clearly articulating the product strategy to stakeholders Key Responsibilities Drive the Ray Data product roadmap - Balance open source Ray Data feature development with Anyscale Runtime commercial differentiation to ensure that both Ray Data becomes the open source standard for AI data processing and Anyscale Runtime remains sufficiently compelling. Drive open source Ray Data adoption - Focus on community growth, developer experience, and ecosystem integrations Market Positioning & Enablement - Work closely with Product Marketing on strategic market positioning, field enablement, and competitive analysis to maintain differentiation. Customer engagement - Drive key customer engagements assisting sales and field engineering teams. Required Qualifications 4+ years of product management experience with technical products Strong technical background in distributed systems, ML infrastructure, or data processing Experience working

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Synthesia
πŸ“ Londonβ€’ Full-timeβ€’ From €180K/yr
1mo ago

Synthesia is the world’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. About the role Lead the delivery of complex engineering projects focused on driving user acquisition, activation, and revenue growth. Break down initiatives into manageable stages with predictable timelines, making clear trade-offs between speed, experimentation, and long-term scalability. Partner closely with product and data to prioritize high-impact work and maximize business outcomes. Understand engineering levelling and scale the team by identifying and filling skill gaps, particularly in areas like experimentation, performance, and conversion optimization. Collaborate with recruiting to attract and retain top talent aligned with Growth’s fast-paced, outcome-driven environment. Monitor team performance proactively, ensuring strong execution and continuous improvement. Support engineers in delivering measurable impact and developing their careers through ownership of key growth metrics. Navigate difficult conversations with clarity and empathy, especially when balancing business urgency with technical quality. Foster a collaborative, high-velocity team culture aligned with company goals. Team you would be leading – Growth The Growth team is dedicated to driving high NDR and sustainable revenue growth through

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Synthesia
πŸ“ Indiaβ€’ Full-time
1mo ago

Synthesia is the world’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 you’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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