2 ΡΠ°ΡΠ° Π½Π°Π·Π°Π΄
DS/ML Engineer (AI)
ΠΡΡΡ & Π‘ΠΎΠΏΡΠΎΠ²ΠΎΠ΄
ΠΠ»Ρ ΠΌΡΡΡΠ° Ρ ΡΡΠΎΠΉ Π²Π°ΠΊΠ°Π½ΡΠΈΠ΅ΠΉ Π½ΡΠΆΠ΅Π½ Plus
ΠΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ
Π’Π΅ΠΊΡΡ:
TL;DR
DS/ML Engineer (AI): Building and shipping production machine-learning systems for an AI engineering intelligence platform with an accent on evaluation systems, model routing, statistical measurement, and MLOps. Focus on calibrating LLM-as-judge systems, balancing inference cost and quality, improving noisy signals, and monitoring deployed models for drift and quality decay.
Location: On-site in Bangalore, India
Company
is building Tetriz, an AI engineering intelligence platform that measures the use and impact of AI coding tools and helps engineering leaders demonstrate AI ROI.
What you will do
- Build evaluation systems for AI features, including failure taxonomies, LLM-as-judge rubrics, golden datasets, and calibration against human judgment.
- Design and evaluate model-routing strategies that balance cost, quality, and latency.
- Turn noisy real-world signals into statistically rigorous, calibrated, and monitored scores.
- Work across the ML lifecycle, including feature pipelines, model versioning, rollouts, drift monitoring, and reliable low-latency serving.
- Contribute to product decisions and ship backend or frontend code when needed.
Requirements
- 1.5β2 years of hands-on experience in data science, machine learning, software engineering, or a related eld.
- Experience building and shipping DS/ML systems end to end through professional work, personal projects, research, or open source.
- Comfort with Python and working knowledge of SQL.
- Basic applied statistics knowledge, including understanding when metrics may be misleading.
- Curiosity about product, backend, and frontend development beyond the modeling layer.
- Some exposure to LLMs through prompting, APIs, or experimentation 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.
hirify.globalts">Culture & Benets
- Builder-oriented environment focused on shipping a complete product rather than conducting research only.
- Inclusive culture that values diversity and merit-based employment.
- AI tools may support parts of the hiring process, while nal decisions remain with human reviewers.
ΠΡΠ΄ΡΡΠ΅ ΠΎΡΡΠΎΡΠΎΠΆΠ½Ρ: Π΅ΡΠ»ΠΈ ΡΠ°Π±ΠΎΡΠΎΠ΄Π°ΡΠ΅Π»Ρ ΠΏΡΠΎΡΠΈΡ Π²ΠΎΠΉΡΠΈ Π² ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ iCloud/Google, ΠΏΡΠΈΡΠ»Π°ΡΡ ΠΊΠΎΠ΄/ΠΏΠ°ΡΠΎΠ»Ρ, Π·Π°ΠΏΡΡΡΠΈΡΡ ΠΊΠΎΠ΄/ΠΠ, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡΠ΅ ΡΡΠΎΠ³ΠΎ - ΡΡΠΎ ΠΌΠΎΡΠ΅Π½Π½ΠΈΠΊΠΈ. ΠΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎ ΠΆΠΌΠΈΡΠ΅ "ΠΠΎΠΆΠ°Π»ΠΎΠ²Π°ΡΡΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡΠΈΡΠ΅ Π² ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΡ. ΠΠΎΠ΄ΡΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β
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