2 Serverless Infrastructure Jobs

You are a highly experienced Lead Machine Learning Engineer specializing in Speech AI, Natural Language Processing (NLP), and Generative AI (GenAI). Your role is crucial in designing and expanding a production-grade speech-based virtual assistant powered by Large Language Models (LLMs), advanced audio signal processing, and multimodal intelligence. Collaborating closely with product, research, and DevOps teams, you will lead a group of ML engineers to create and implement cutting-edge AI solutions. In this role, your responsibilities include architecting and implementing advanced machine learning models for speech recognition (ASR), text-to-speech (TTS), NLP, and multimodal tasks. You will lead the development and fine-tuning of Transformer-based LLMs, including encoder-decoder architectures for audio and text tasks. Additionally, you will build custom audio-LLM interaction frameworks incorporating modality fusion, speech understanding, and language generation techniques. Your duties also involve designing and deploying LLM-powered virtual assistants with real-time speech interfaces for dialog, voice commands, and assistive technologies. You will integrate speech models with backend NLP pipelines to handle complex user intents, contextual understanding, and response generation effectively. Furthermore, you will design and implement end-to-end ML pipelines covering data ingestion, preprocessing, feature extraction, model training, evaluation, and deployment. Developing reproducible and scalable training pipelines using MLOps tools such as MLflow, Kubeflow, and Airflow with robust monitoring and model versioning will be part of your responsibilities. You will also drive CI/CD for ML workflows, model containerization (Docker), and orchestration using Kubernetes/serverless infrastructure. To stay updated with the latest advancements in Speech AI, LLMs, and GenAI, you will evaluate and drive the adoption of novel techniques. Experimenting with self-supervised learning, prompt tuning, parameter-efficient fine-tuning (PEFT), and zero-shot/multilingual speech models will be essential for innovation and progress. The required technical skills for this role include: - 10+ years of hands-on experience in machine learning, with a deep focus on audio (speech) and NLP applications. - Expertise in Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) systems, including tools like Wav2Vec, Whisper, Tacotron, FastSpeech, etc. - Strong knowledge of Transformer architectures like BERT, GPT, T5, and encoder-decoder LLM variants, including training/fine-tuning at scale. - Proficiency in Python programming and deep learning frameworks like PyTorch and TensorFlow. - In-depth understanding of audio signal processing concepts such as MFCCs, spectrograms, wavelets, sampling, filtering, etc. - Experience with multimodal machine learning, including the fusion of speech, text, and contextual signals. - Deployment of ML services with Docker, Kubernetes, and experience with distributed training setups on GPU clusters or cloud platforms (AWS, GCP, Azure). - Proven experience in building production-grade MLOps frameworks and maintaining model lifecycle management. - Experience with real-time inference, latency optimization, and efficient decoding techniques for audio/NLP systems. Preferred qualifications for this role include: - Master's or Ph.D. in Computer Science, Machine Learning, Signal Processing, or related technical discipline. - Publications or open-source contributions in speech, NLP, or GenAI. - Familiarity with LLM alignment techniques, RLHF, prompt engineering, and fine-tuning using LoRA, QLoRA, or adapters. - Previous experience in deploying voice-based conversational AI products at scale.,

At Kodo, we believe that managing a fast-growing company's finances and operations shouldn't feel like a juggling act. That's why we offer a single platform to streamline all purchase processes for businesses, providing them with everything they need to save time, cut costs, and scale easily. Trusted by companies such as Cars24, Mensa Brands, Zetwerk, and many more, Kodo transforms financial chaos into clarity. Our teams are empowered with flexible corporate processes while integrating effortlessly with their ERPs for real-time insights. We have raised $14M from investors such as Y Combinator, Brex, and other global investors. Our mission is to simplify the CFO stack for fast-growing businesses. We believe in creating exceptional products for our customers, an enriching environment for our team, and a solid business that grows profitably. What you'll be doing: - Ensure that our applications and environments are stable, scalable, secure, and performing as expected. - Proactively engage and work in alignment with cross-functional colleagues to understand their requirements, contributing to and providing suitable supporting solutions. - Develop and introduce systems to aid and facilitate rapid growth, including implementation of deployment policies, designing and implementing new procedures, configuration management, and planning of patches and capacity upgrades. - Ensure suitable levels of monitoring and alerting are in place to keep engineers aware of issues. - Establish runbooks and procedures to minimize outages, jumping in before users notice issues and automating processes for the future. - Automate tasks to ensure nothing is done manually in production. - Identify and mitigate reliability and security risks, preparing for peak times, DDoS attacks, and potential errors. - Troubleshoot issues across the entire stack - hardware, software, applications, and network. - Manage individual project priorities, deadlines, and deliverables as part of a self-organizing team. - Continuously learn and exchange knowledge by conducting code reviews, participating in retrospectives, and staying updated with new insights. You Must Have: - 2+ years of extensive experience in Linux server administration, including patching, packaging, performance tuning, networking, user management, and security. - 2+ years of implementing systems that are highly available, secure, scalable, and self-healing on the Azure cloud platform. - Strong understanding of networking, especially in cloud environments. - Prior experience implementing industry-standard security best practices, including those recommended by Azure. - Proficiency in Bash and any high-level scripting language. - Proficiency in Infrastructure as Code and Infrastructure Testing, preferably using Pulumi. - Hands-on experience in building and administering VMs and Containers using tools such as Docker/Kubernetes. - Excellent communication skills, both spoken and written, with the ability to articulate technical problems and projects to stakeholders. Extra credits for: - Experience with serverless infrastructure and Azure infra. - Experience in governance processes and compliance validation, especially for financial services. - Experience working in product startups. - Experience in administering and scaling PostgreSQL.,