ML Researcher (remote)

Role overview Work on the research team building and evaluating machine learning models for enterprise decision-making, contributing to the full lifecycle from ideation through deployment. The role combines cutting-edge research with solid engineering, helping shape architectures, training methods, and evaluation protocols for large-scale models that operate on structured, tabular data.

Responsibilities - Ideate, design, implement, and evaluate new machine learning models intended for real-world production use. - Drive model performance end-to-end, including novel architectures, training recipes, and inference efficiency. - Define and refine evaluation protocols that accurately measure model quality and reliability. - Develop engineering practices and research infrastructure that enable rapid experimentation across the team. - Contribute to scaling up models and training regimes using GPUs, TPUs, or distributed training systems. - Collaborate with other researchers to test, validate, and iterate on shared ideas.

Requirements - Strong familiarity with the full research cycle in machine learning, from problem framing to publication or deployment. - Solid software engineering fundamentals and clean, maintainable research code. - Deep knowledge of Python and its primary ML frameworks. - Experience with the full AI model development lifecycle and modern ML infrastructure tooling. - Hands-on experience developing new ML methods, algorithms, and models. - Practical experience with GPU or TPU training and distributed training setups. - Working knowledge of classical ML methods and modern deep learning techniques.

Nice to have - Specialized expertise in architecture research, distillation or model compression, evaluation, code generation, or LLMs. - Experience with foundation models such as large language models. - Published research at major AI conferences or contributions to open source ML projects. - Background in tabular data, predictive analytics, or high rankings on competitive ML platforms. - BSc, MSc, or PhD in computer science, machine learning, or a closely related field.

Benefits and work setup - Competitive compensation combining salary and equity. - Comprehensive health coverage for employees and their dependents. - Paid parental leave for all new parents, including adoptive and surrogate journeys. - Relocation support for employees joining an office hub. - Mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action.