Overview

\nThe Senior Machine Learning Researcher is a high-impact individual contributor role responsible for leading complex research initiatives and developing cutting-edge machine learning methodologies.

Responsibilities

• \nPosition Summary
• \nThe Senior Machine Learning Researcher is a high-impact individual contributor role responsible for leading complex research initiatives and developing cutting-edge machine learning methodologies. This position plays a key role in shaping AI roadmap by delivering novel, production-ready ML solutions that advance product capabilities and improve customer outcomes.
• The Senior Machine Learning
• Researcher is a key driver of AI innovation, shaping both the research agenda and the technical growth of the team. In addition to direct technical contributions, this role provides mentorship and technical leadership for junior researchers, helping to foster a culture of innovation, rigor, and knowledge sharing across the team Responsibilities: Research Leadership
• \n● Lead end-to-end ML research projects, from problem definition through experimentation, model design, evaluation, and deployment.
• \n● Identify novel techniques, architectures, or workflows that unlock new product capabilities or improve current systems.
• \n● Design and guide comparative studies, benchmarks, and feasibility assessments for emerging methods. Note: ML Researcher needs to handle building custom color models for specific customers as well as image-related models for features added to the application. Technical Execution ● Implement scalable, performant training pipelines using state-of-the-art frameworks (e.g., PyTorch, JAX).
• \n● Own the development of complex models including embeddings, transformers, diffusion models, or multi-modal systems where applicable.
• \n● Collaborate with ML Engineers and MLOps to integrate research outputs into production-grade systems. Mentorship & Technical Stewardship
• \n● Act as a mentor and technical advisor to ML Researcher I/II team members; must have directly contributed to the promotion of at least one ML Researcher I to II.
• \n● Provide peer review of code, experimental design, and results; set standards for research documentation and reproducibility.
• \n● Help define best practices and technical strategy for the broader ML function. Cross-Functional & Strategic Collaboration
• \n● Engage with Product and Engineering teams to align research with product vision and practical user needs.
• \n● Partner with Data Engineering to define new datasets or labeling strategies to support advanced ML pipelines.
• \n● Contribute to long-term planning for ML investments and team capacity.
• \nRequirements:
• \n● M.Sc. in Machine Learning, Computer Science, Applied Mathematics, or a related field with 5–6 years of industry experience
• \n● OR Ph.D. in a relevant field with 2–3 years of post-graduate industry experience
• \n● Demonstrated ownership of ML research projects from design through deployment
• \n● Strong expertise in areas such as deep learning, generative modeling, time series, computer vision, or large language models ● Proven experience mentoring junior researchers, including at least one promotion from ML Researcher I → II ● Proficient in Python and modern ML tooling (e.g., PyTorch, JAX, HuggingFace, Weights & Biases, etc.) ● Familiarity with production constraints (latency, memory, real-time inference) and model lifecycle management