Machine Learning Engineer
SweedFull Time
Mid-level (3 to 4 years)
Candidates must possess strong programming skills in Python, Rust, or Go, and have experience with AI/ML model training and serving pipelines using frameworks like PyTorch, JAX, or TensorFlow. A solid foundation in distributed systems, networking, or applied cryptography is essential, along with familiarity with concepts such as federated learning, secure aggregation, or verifiable intelligence. Experience with blockchain protocols, zkML, or decentralized networks is considered a bonus.
The Research Engineer will design and implement protocols for decentralized AI training and inference, including federated learning, distributed fine-tuning, and secure model serving. Responsibilities include building scalable systems for AI workloads across heterogeneous networks and devices, contributing to architectural decisions, performance optimization, and reliability engineering, and collaborating with researchers and system engineers to translate novel ideas into real-world systems. The role also involves staying current with advancements in AI, distributed infrastructure, and cryptographic mechanisms.
Energy-efficient window ACs and heat pumps
Gradient Comfort creates energy-efficient window air conditioners that also function as heat pumps, providing both cooling and heating without obstructing views. Their products use R-32 refrigerant, which is more environmentally friendly than traditional options, making them appealing to eco-conscious consumers, especially in regions with strict emissions regulations like New York. Unlike competitors, Gradient Comfort sells directly to consumers through its website, fostering a closer relationship with customers. The company's goal is to lead in clean energy innovation and support decarbonization efforts in home climate control.