Data Scientist focused on large-scale recommendation systems and agentic AI at Glance.
Responsibilities
Design and develop large-scale recommendation systems using advanced ML, statistical modeling, ranking algorithms, and deep learning.
Build and operate machine learning models on diverse, high-volume data sources for personalization, prediction, and content understanding.
Develop rapid experimentation workflows to validate hypotheses and measure real-world business impact.
Own data preparation, model training, evaluation, and deployment pipelines in collaboration with engineering counterparts.
Monitor ML model performance using statistical techniques; identify drifts, failure modes, and improvement opportunities.
Requirements
Bachelor’s/Master’s in Computer Science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or related fields. PhD is a plus.
Own the data access and integration experience of the platform: how data gets in, how it is accessed, and how consuming teams integrate with it. You will be the decision-maker for your area and work with engineers, architects and UX to take products from concept to launch.
Responsibilities
Act as the authoritative product owner for one or more data access and integration areas, leading discussions to a clear recommendation or decision.
Build a shared vision and consensus on priorities across the company.
Define and analyze the metrics that show whether your products succeed.
Guide one or more engineering teams from ideation through launch of data ingestion, access and integration capabilities.
Write product requirements from a user and functional perspective, with scope, supported patterns and acceptance criteria that engineering can build against.
Build the models and agents behind the intelligence that powers TRM's products, including training foundation models on blockchain data and building autonomous AI agents.
Responsibilities
Train ML models on blockchain data, including foundation models, and take them from research to production
Build AI agents (and fine-tune LLMs where it helps) so the intelligence underneath TRM's products is generated by models and agents, not only hand-built heuristics
Find new ways to generate net new intelligence, using patterns across all intelligence layers (Network / On-chain / Protocol) that competitors can't replicate
Ship production-quality code: ML models, agents and data pipelines, with rigorous evaluation and scalable architecture
Take on ambitious, high-impact bets that raise the ceiling of what our intelligence can do, and drive measurable outcomes: billions in illicit funds traced, seized, or prevented
Lead architecture, design, and delivery of large‑scale data platforms, pipelines, and products supporting complex business capabilities across multiple domains.
Locations (2)
Bangalore, Karnataka, India
Chennai, Tamil Nadu, India
Responsibilities
Lead architecture, design, and delivery of large‑scale data platforms, pipelines, and products
Translate ambiguous business and operational problems into well‑defined data solutions
Drive execution of multiple business plans and projects
Build and optimize reliable batch and streaming data pipelines
Design scalable data models across relational, dimensional, NoSQL, data lake, and warehouse platforms
Lead the architecture, design, and delivery of large‑scale data platforms, pipelines, and products supporting complex business capabilities across multiple domains.
Locations (2)
Bangalore, Karnataka, India
Chennai, Tamil Nadu, India
Responsibilities
Lead architecture, design, and delivery of large‑scale data platforms, pipelines, and products
Translate ambiguous business and operational problems into well‑defined data solutions
Drive execution of multiple business plans and projects
Build and optimize reliable batch and streaming data pipelines
Design scalable conceptual, logical, and physical data models
Lead the technical direction of the search engine behind Progress’s Agentic RAG product, designing and implementing distributed Rust-based search and indexing systems.
Compensation
Generous remuneration package
Employee Stock Purchase Plan Enrollment
Vacation, Family, and Health
23 vacation days annually
Birthday day off
Community service time off
International Women's Day - March 8 is an official holiday for all employees
Life and Medical Insurance
Responsibilities
Own the architecture and roadmap of our distributed search and indexing engine, written in Rust.
Design and implement vector, full-text and graph indexes (HNSW, quantization, multi-vector, Tantivy) and the query and filtering layer on top of them.
Evolve how indexes are built, merged, sharded and replicated on object storage, PostgreSQL and NATS.
Lead large migrations and performance work, based on profiling and benchmarks, without customer downtime.
Contribute to the Python services, SDKs and PyO3 bindings built on the engine, keeping public APIs stable.
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