DS / ML Engineer
Tetriz
Bangalore, IndiaPosted 1 month ago
Skill Required
DS/MLMachine Learning EngineerMachine LearningObservabilityStatisticsPythonGitGenerative AISQLFulltime
Key highlights
- 1.5–2 years of required experience in DS/ML/SE or related
- Builder mindset with cross-functional contributions
Role overview
Tetriz is an AI Engineering Intelligence platform that helps engineering organizations become AI-native by measuring the usage of AI coding tools, improving engineer effectiveness through coaching, and demonstrating AI ROI with defensible insights. This role is centered around a builder mindset, focusing on ML systems as the primary craft while also contributing to product development, backend/frontend code, and data pipelines. The ideal candidate thrives on breadth and is energized by working across various aspects of the product rather than staying in a specialized lane.
Responsibilities
- Build evaluation systems for AI features, including failure taxonomies, LLM-as-judge rubrics, golden datasets, and calibration against human judgment
- Ensure automated scores remain honest as models and prompts evolve
- Work on model routing and inference economics, balancing cost, quality, and latency per task
- Run experiments to justify model routing choices and catch regressions
- Turn noisy, real-world signals into trustworthy scores grounded in statistical rigor
- Move heuristic-driven approaches toward calibrated, monitored systems
- Work on the full MLOps lifecycle: feature pipelines, model versioning, rollout, and monitoring for drift and silent quality decay
- Collaborate with engineering to ensure models are served reliably at low latency
Requirements
- 1.5–2 years of hands-on experience in Data Science, Machine Learning, Software Engineering, or a related role
- Experience building and shipping DS/ML systems end-to-end through professional work, personal projects, research, or open-source contributions (not just notebooks)
- Comfort with Python and working SQL knowledge
- Basic grounding in applied statistics — ability to explain what a metric means and when it might be misleading
- A builder's instinct — genuine curiosity about product decisions, backend, or frontend, not just the modeling layer
- Some exposure to LLMs — prompting, using APIs, or experimenting with model behavior
Nice to have
- Exposure to evaluation or observability tooling for LLM features
- Experience with information retrieval, entity-matching, or record-linkage
- Interest in developer-productivity, code analytics, or DevEx data
Additional details
- We aspire to create an inclusive culture of diverse people not just because it's the right thing to do but because heterogeneity inspires us and is more fun!
- We employ people solely on merit and do not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression