Mountain View, California, United States · On-site
$150k–$250k/yr
We are looking for a Member of Technical Staff with strong Python skills and a passion for building scalable platforms for AI and ML workloads. As MTS, you'll influence strategic decisions, partner closely with the found…
Skills: Python, FastAPI, Distributed Systems, SQL, NoSQL
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Architect and develop scalable software infrastructure optimized for high-performance AI and ML workloads. Lead the end-to-end delivery of product features and define efficient microservice architectures.
Requires deep expertise in Python, distributed systems, and database management (SQL/NoSQL). Candidates should have a proven track record of implementing CI/CD pipelines and owning complex product features.
We are looking for a Member of Technical Staff with strong Python skills and a passion for building scalable platforms for AI and ML workloads. As MTS, you'll influence strategic decisions, partner closely with the founding team, and play a critical role in shaping Activeloop's AI infrastructure.
Architect and Develop: Design and build scalable software infrastructure optimized for high-performance AI and ML workloads, ensuring robustness and maintainability.
Lead Feature Development: Own end-to-end delivery of key product features, from initial concept through deployment and support.
Innovate APIs and Microservices: Define efficient RESTful APIs and microservice architectures tailored to customer-driven use cases.
Scale Distributed Systems: Implement systems designed for high-throughput, low-latency, large-scale data processing.
Enhance Scalability: Drive strategic evolution of system architecture to proactively handle future scalability and performance demands.
Implement CI/CD Pipelines: Develop streamlined CI/CD workflows for rapid testing, deployment, and feature iteration.
Collaborate with Technical Founder: Directly influence engineering strategy and roadmap decisions through close collaboration with the technical founder.
Partner Cross-functionally: Work closely with ML, frontend and backend engineers to seamlessly deliver features aligned with business objectives.
Enhance Reliability: Ensure platform reliability and uptime through advanced monitoring, logging, and alerting using modern DevOps tools (Docker, Kubernetes, AWS, GCP, Azure).
Deep expertise in Python and modern software frameworks (e.g., FastAPI).
Solid understanding of distributed systems, ideally applied to AI workloads
Strong knowledge of SQL and NoSQL databases (PostgreSQL, Redis, MongoDB).
Experience building RESTful APIs and microservices
Demonstrated capability in implementing CI/CD pipelines and DevOps practices.
Exceptional communication, collaboration, and problem-solving skills.
History of owning complex product features from inception through support.
Hands-on experience with GPU performance optimization, CUDA or Triton kernels, or profiling AI workloads.
Proven comfort with ambiguity, rapid iteration, and adaptive decision-making in startup environments.
Enthusiasm for directly incorporating customer feedback into product development.
Proactive in anticipating technical challenges and providing innovative solutions.
This role is open to a range of experience levels. New graduates with strong fundamentals and impressive projects are encouraged to apply.
Deep Lake: Database for AI
Deep Lake is a Database for AI powered by a unique storage format optimized for deep-learning and Large Language Model (LLM) based applications (http://github.com/activeloopai/deeplake; 8K+ stars). It simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage for all workloads, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more. Deep Lake works with data of any size, it is serverless, and it enables you to store all of your data in one place. Deep Lake is used by Intel, Matterport, Hercules.ai, Red Cross, Yale, & Oxford. Try out Deep Lake today via app.activeloop.ai Activeloop's founding team is from Princeton, Stanford, Google, and Tesla, and is backed by Y Combinator.
Offices: 196 Castro St, Mountain View, California 94041, US
Deep Lake: Database for AI
Deep Lake is a Database for AI powered by a unique storage format optimized for deep-learning and Large Language Model (LLM) based applications (http://github.com/activeloopai/deeplake; 8K+ stars). It simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage for all workloads, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more. Deep Lake works with data of any size, it is serverless, and it enables you to store all of your data in one place. Deep Lake is used by Intel, Matterport, Hercules.ai, Red Cross, Yale, & Oxford. Try out Deep Lake today via app.activeloop.ai Activeloop's founding team is from Princeton, Stanford, Google, and Tesla, and is backed by Y Combinator.
Offices: 196 Castro St, Mountain View, California 94041, US