The Role
Leads end-to-end machine learning research, including problem definition, experimentation, model development, evaluation, and production deployment. Develops advanced models and scalable training pipelines using modern frameworks, collaborates with ML Engineering, MLOps, Product, and Data Engineering, and defines datasets and labeling strategies. Mentors junior researchers, reviews technical work, establishes reproducibility standards, and contributes to AI strategy, roadmap planning, and team development.
Summary Generated by Built In
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
Skills Required
- M.Sc. in Machine Learning, Computer Science, Applied Mathematics, or a related field, with 5–6 years of industry experience
- Alternatively, a Ph.D. in a relevant field with 2–3 years of post-graduate industry experience
- Demonstrated ownership of machine learning research projects from design through deployment
- Strong expertise in deep learning, generative modeling, time series, computer vision, or large language models
- Proven experience mentoring junior researchers, including promoting at least one ML Researcher I to ML Researcher II
- Proficiency in Python and modern machine learning tooling, such as PyTorch, JAX, Hugging Face, and Weights & Biases
- Familiarity with production constraints, including latency, memory, real-time inference, and model lifecycle management
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Blackbuck Insights is a global data and AI consultancy providing data engineering services, cloud modernization, AI activation, and platform operations. The company helps enterprises modernize legacy environments, migrate and scale data platforms, build AI-enabled business applications, and establish trusted data foundations for analytics and intelligent decision-making. Its services support organizations seeking reliable, performant, and scalable technology solutions.
