No longer accepting applicationsThis role at Sber has closed. Browse live web3 jobs instead.
Get Discovered
No applications. Teams find and message you directly.
Get discovered. Join the talent poolNo account needed · 0 people in the pool→
No account needed. Teams find you and reach out directly.
0 people already in the pool
◆ 6/10
aitechfintechML Engineer
Join Talent Pool
Subscribe to our Telegram channel
✓ Direct apply: you message the hiring person. No ATS.
About this role
Join Sber as an ML Engineer to design and develop AI agents, transform Data Science prototypes into reliable solutions, and work with large data volumes using SQL, Hadoop, and Spark.
Description
Join Sber as an ML Engineer to design and develop AI agents, transform Data Science prototypes into reliable solutions, and work with large data volumes using SQL, Hadoop, and Spark.
Responsibilities
Responsibilities
- Design and develop AI agents: implement scenarios, orchestration, tool calling, and integrations with internal services.
- Transform prototypes and Data Science models into reliable industrial solutions: package, integrate into services and pipelines, version, and maintain.
- Develop services, libraries, and pipelines in Python, write automated tests, and participate in code reviews.
- Design, build, and maintain data showcases for ML models and agents.
- Process large volumes of data using SQL, Hadoop, and Spark; optimize queries and computational tasks.
- Ensure quality and observability of solutions: logging, monitoring, error handling, and data quality control.
Requirements
Requirements
- At least 2 years of industrial development experience in Python.
- Ability to write maintainable code: typing, testing, error handling, logging, and dependency management.
- Proficient in SQL: complex queries, window functions, optimization, and working with large datasets.
- Experience in building and maintaining ETL/ELT pipelines and data showcases.
- Experience in deploying services, models, or data products into production.
- Understanding of AI agent principles: orchestration, tool calling, state management, and API integration.
- Understanding of the ML model lifecycle — from artifacts and data to inference, monitoring, and updates.
- Experience in developing AI agents using LangGraph, LangChain, LlamaIndex, or custom orchestrators (a plus).
- Experience with LLM, RAG, and vector storage (a plus).
- Experience orchestrating pipelines in Airflow or similar systems (a plus).
- Experience with Kafka and event-driven architectures (a plus).
- Knowledge of Docker, CI/CD, and Kubernetes (a plus).
- Practical experience with Hadoop and Spark (a plus).
- Experience implementing ML or LLM services in an internal environment (a plus).
- Experience in the banking domain, products for legal entities, or document flow (a plus).
Job Details
Market range (est.)$90k–$180k
LocationHybrid
AI Score★★★★★★☆☆☆☆ 6/10
PostedSep 23, 2026 (7h ago)
Tags & Skills
aitechfintechML Engineerhybrid
Tech Stack
PythonSQLHadoopSparkDockerCI/CDKubernetes
Join Talent Pool
Subscribe to our Telegram channel
✓ Direct apply: you message the hiring person. No ATS.