Senior ML Research Engineer

Position Summary

• The 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

• Lead end-to-end ML research projects, from problem definition through

experimentation, model design, evaluation, and deployment.

• Identify novel techniques, architectures, or workflows that unlock new

product capabilities or improve current systems.

• 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).

• Own the development of complex models including embeddings,

transformers, diffusion models, or multi-modal systems where applicable.

• Collaborate with ML Engineers and MLOps to integrate research

outputs into production-grade systems.

Mentorship & Technical Stewardship

• 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.

• Provide peer review of code, experimental design, and results; set

standards for research documentation and reproducibility.

• Help define best practices and technical strategy for the broader ML function.

Cross-Functional & Strategic Collaboration

• Engage with Product and Engineering teams to align research with product

vision and practical user needs.

• Partner with Data Engineering to define new datasets or labeling

strategies to support advanced ML pipelines.

• Contribute to long-term planning for ML investments and team capacity.

Requirements

• M.Sc. in Machine Learning, Computer Science, Applied Mathematics, or a

related field with 5–6 years of industry experience

• OR Ph.D. in a relevant field with 2–3 years of post-graduate industry experience
• Demonstrated ownership of ML research projects from design through deployment
• 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