As a Lead Machine Learning Engineer, be the technical authority for our most ambitious client projects. Set the technical vision, guide teams of talented engineers, and translate complex business challenges into cutting-edge AI solutions on Google Cloud. Be an advocate of high-quality engineering and best-practice in production software as well as rapid prototypes. This is a hands-on leadership role.
Build our AI platform, training custom computer vision models to predict equipment failures and risks, boosting efficiency and safety in industrial settings. Shape our tech stack, deploying cutting-edge AI models to real-world systems integrating real-time sensor and camera data. Your responsibilities will vary from week to week as priorities evolve.
We're seeking a proactive problem solver who loves hands-on coding. This role is at the intersection of conversational AI, radar technology, hardware integration, and neural networks. You'll be crucial to our product's success, starting with developing and refining our proprietary algorithms that use radar signals for vital signs detection. You'll also explore our entire tech stack for new innovation opportunities.
This Senior AI Engineer will build believable AI behaviors, as well as architect and maintain the systems which support AI characters in the world. You will work alongside designers to craft these AI systems and will play a meaningful role in driving the innovation of our AI.
The role focuses on applied algorithms and engineering — using recent advances in DL/LLMs to develop new features and products. This role provides an opportunity to work on cutting-edge LLM technologies, deploy impactful solutions in production, and shape the future of AI-driven features and products at Gloass.ai.
Deliver the right content to the right user at the right time through push, email, and in-app notifications. Tackle unique ML challenges at Reddit scale: recommend from hundreds of millions of posts, optimize across channels, and balance relevance, timeliness, and user fatigue. Build and productionize large-scale retrieval, ranking, and budgeting models that personalize notifications for tens of millions of users.
Be a technical leader within the team and within Spotify, coordinating projects across teams. Facilitate collaboration with engineers, product owners, and designers to solve challenging problems. Architect, design, develop, and deploy ML models for podcast recommendations across surfaces. Be a leader in Home’s ML community, working efficiently within existing platforms and systems.
Seeking a Machine Learning Engineer to join our advanced model development team, focusing on pre-training, continued training, and post-training of models, with emphasis on draft model optimization for speculative decoding and quantization-aware training (QAT). The ideal candidate has deep experience with training methodologies, open-weight models, and performance-tuning for inference.
You will play a key role in supporting teams of applied scientists and ML developers who train, evaluate, and use a variety of NLP models, including LLMs. Your mission is to contribute to prototyping, productionizing, and maintaining the NLP technologies that power some of Coveo's most visible AI capabilities. Participate directly in every aspect of NLP technology delivery.
You’ll help build the intelligent systems that power this mission - from personalized recommendations and fraud detection to automation and search. You’ll join a fast-paced, flat team structure where your execution and ideas shape real-world outcomes every day. Your work will directly impact user experience, efficiency, and platform intelligence.