Remote Software engineering Jobs · TensorFlow

• Design, build, and productionize ML models for fine-tuned, Retrieval-Augmented Generation (RAG), and generative AI features.
• Build and maintain scalable data pipelines to collect high-quality training and evaluation datasets, including annotation systems and human-in-the-loop workflows.
• Collaborate with product and engineering to iterate on datasets, evaluation metrics, and model architectures to improve quality and relevance.

• Build and design end-to-end training pipelines for AI models, covering data ingestion to inference.
• Architect scalable inference systems using tools like vLLM, TensorRT-LLM, or DeepSpeed.
• Shape early product direction by experimenting with new use cases and building AI-powered experiences.

• Design, build, and deploy machine learning models for personalization, automation, and insights.
• Manage the full ML lifecycle: data preprocessing, feature engineering, training, tuning, evaluation, deployment.
• Integrate ML outputs into user-facing products and backend systems.

• Design, build, and ship production-grade ML models for high-impact use cases.
• Lead model architecture decisions, data pipeline design, and deployment strategies.
• Collaborate across product, engineering, and data teams to drive AI initiatives end-to-end.

As an Associate Machine Learning Engineer, you will help develop AI and ML systems that improve how Spotify detects, reviews, and manages risky or non-compliant activity. You’ll work with engineers, data scientists, and policy partners to design and evaluate models, automate performance tracking, and enhance transparency and auditability. This is a hands-on, collaborative role where you’ll learn from experienced practitioners while building solutions that advance safety, compliance, and responsible innovation.

• Research and develop computer vision and deep learning models.
• Build and maintain training and inference pipelines using frameworks like PyTorch or TensorFlow.
• Evaluate model performance using real-world data and optimize for accuracy, speed, and scalability.

• Design, develop, and implement novel machine learning models and algorithms tailored to specific challenges.
• Engineer and deploy ML models into production environments, ensuring they are robust and scalable.
• Develop and maintain MLOps infrastructure for model versioning, continuous integration/delivery, and automated monitoring.

Lead the development and deployment of advanced AI models and systems. Oversee software development teams (30+ engineers) across multiple product lines. Coach and develop talent and foster a culture of excellence.

Design, implement, and optimize machine learning and computer vision algorithms for livestock management. Collaborate with cross-functional teams to integrate algorithms into production systems. Research and apply the latest computer vision and machine learning techniques to improve system performance.

Drive the technical evolution of our AI-first platform and serve as our resident expert. You won't just be tuning hyperparameters in a notebook; you will be a core software engineer architecting the complex systems that make AI useful in production. Craft complex AI processing architectures and hands-on data/backend engineering.