Job VC
Senior Data Scientist, Machine Learning Engineer
Technologies
Description
Senior Data Scientist, Machine Learning Engineer
Shelf
Категорії:
Data
,
Python
Senior
Дистанційна робота
Lviv
Місцезнаходження:
Дистанційна робота
Lviv
Пропозиція дійсна до: 14.06.2026 (залишилося 30 днів)
Вакансія з додатк. підтримкою біженців
Працодавець надає додаткові бенефіти для підтримки біженців у зв’язку з ситуацією в Україні, враховуючи один або декілька з наступних варіантів:
співбесіди українською,
прискорений процес рекрутації,
релокаційний пакет,
психологічна підтримка,
будь-який інший варіант, залежно від роботодавця та кандидата
Необхідні знання
Python
NLP
RESTful
LLM
SQL
NoSQL
pandas
NumPy
ETL
Data analysis
Англійська
(C1)
Буде плюсом
AWS ML stack
Pinecone
Elasticsearch
pgvector
FAISS
DeepLake
GitHub
Наші вимоги
Оригінальний текст.
Показати переклад
3+ years of professional experience researching and shipping ML-based solutions, with strong Python skills and a track record of delivering fast without sacrificing quality
Proven experience in owning research problems end-to-end, starting from initial data analysis, through iterative research phases to delivering on production
Practical NLP/LLM experience: transformers, embeddings, prompt design, and evaluation; ability to choose and justify metrics and methodologies
Strong backend fundamentals: designing RESTful services, schema design, data modeling, and performance tuning for SQL and NoSQL stores
Data processing skills: pandas/NumPy; experience with batch/stream processing and ETL orchestration (e.g., Airflow, Step Functions)
Strong English verbal and written communication
As a plus
LLM ops and safety: eval frameworks (e.g., RAGAS), guardrails, red-teaming, prompt optimization at scale
Model optimization: quantization, distillation, pruning; GPU/accelerator-aware serving
Experience with AWS ML stack (SageMaker, Batch, Step Functions, Lambda, SQS/SNS, DynamoDB, ECS, EC2, S3)
Vector databases and search: Pinecone, Elasticsearch, pgvector, FAISS, or DeepLake
Background in reinforcement learning, agent frameworks, or autonomous agents
Publications, open-source contributions, GitHub portfolio
Про посаду / проект
Оригінальний текст.
Показати переклад
The R&D department plays a pivotal role in driving Shelf to disrupt the market. We are looking for Machine Learning experts that are able to deliver end to end with a blend of experience: Python engineering, ML engineering, and pragmatic Data science and Machine learning research. You will ship end-to-end features—from problem framing and experimentation to service deployment, and ongoing operations—quickly and with high quality. Your work will power ML- and LLM-driven services used by top enterprises like Amazon, Mayo Clinic, AmFam, and Nespresso.
This role requires strong Python engineering capabilities coupled with a strong ability to deliver robust ML solutions, along with ML research literacy to choose sound methodologies, define metrics, and evaluate different approaches effectively.
You’ll work in an agile environment, move fast, and own what you ship.
What Shelf Offers
B2B contract
Company Stock Options
Hardware: MacBook Pro
Modern technical stack. Develop open-source software
Premier AI development environment: GitHub Copilot, Claude Code, OpenAI, TypingMind, v0, MCP Servers, plus credits to experiment with emerging AI tools
About Shelf
There is no AI Strategy without a Data Strategy. Getting GenAI to work is mission-critical for most companies, but 90% of AI projects haven't deployed. Why? Poor data quality—it’s the #1 obstacle companies face getting GenAI into production.
Shelf unlocks AI readiness. We provide the core infrastructure that enables GenAI to be deployed at scale. We help companies deliver more accurate GenAI answers by eliminating bad data in documents and files before they go into an LLM and create bad answers.
We’re partnered with Microsoft, Salesforce, Snowflake, Databricks, OpenAI and other leaders bringing GenAI to the enterprise. Our mission is to empower humanity with better answers everywhere.
Обов'язки
Оригінальний текст.
Показати переклад
Own end-to-end delivery: ideate, research, prototype, productionize, and operate ML-powered services with an expectation to iterate and ship frequently
Stand up robust training/evaluation pipelines: dataset curation, labeling/feedback loops, experiment tracking, offline/online metrics, and A/B testing
Solve problems using sound methodology, evaluate approaches along with
Transform ML models and LLM workflows (including RAG) into reusable, versioned, observable production services with CI/CD
Collaborate with Product Owners to shape our product and requirements
Conduct and receive code reviews; champion engineering excellence, testing discipline, and documentation
показати все
(8)
Деталі
Онлайн-співбесіди
Мова для рекрутингу: українська&англійська
Старт ASAP
Оплачувана відпустка за: B2B
Повністю дистанційна
Гнучкий робочий час
Етапи процесу рекрутингу
0. Intro Call with a recruiter;
1. Tech Screen with a Director of AI
2. Tech Interviews
3. Final Interview
Обладнання
Apple
Комп'ютер: Notebook
Бонуси в офісі
Безоплатна кава
Відсутність дрес-коду
Переваги
Stock options
GitHub Copilot subscription
LLM credits
Невеликі команди
Міжнародні проєкти
Про компанію
Shelf
Transform business operations with agentic AI. An end-to-end system for designing and scaling AI agents.
Заснована в:
2016
Розмір компанії:
50 - 249
Місцезнаходження:
Wrocław + 1
The enterprise is going agentic — but most AI agents fail when they hit real business complexity. Shelf is changing that.
We’ve built the operating system for agentic AI: a platform that models your policies, workflows, and operational logic into an AI Data Model so agents don’t just respond — they reason. The result? AI that understands how your business actually runs and delivers precise, compliant, auditable outcomes at scale.
Brands like Amazon, Nespresso, HelloFresh, and KeyBank trust Shelf to power AI agents that resolve 85% of cases autonomously, cut handle times by 20–25%, and turn hours-long processes into seconds. We’re partnered with Microsoft, Salesforce, OpenAI, Snowflake, and Databricks — and recognized by Gartner (Cool Vendor) and IDC (Innovator) for our approach.
If you want to sell the infrastructure that makes agentic AI actually work in the enterprise, you’re in the right place.
Our mission
is to empower humanity with better answers everywhere.
X XXX - XX XXX PLN
Перевірте, чи є у вас зарплатний метч
> 10k UAH
> 12.5k UAH
> 15k UAH
> 18k UAH
> 20k UAH
> 25k UAH
> 30k UAH
> 40k UAH
> 45k UAH
> 50k UAH
> 55k UAH
> 60k UAH
> 65k UAH
> 70k UAH
> 75k UAH
> 80k UAH
> 85k UAH
> 90k UAH
> 95k UAH
> 100k UAH
> 120k UAH
> 150k UAH
> 170k UAH
> 200k UAH
> 250k UAH
> 270k UAH
> 300k UAH
> 350k UAH
> 370k UAH
> 400k UAH
Діапазон заробітної плати розкриють на першій співбесіді.
Як це працює
Відгукнись
Зберегти вакансію
Налаштувати резюме
BETA
Shelf
Категорії:
Data
,
Python
Senior
Дистанційна робота
Lviv
Місцезнаходження:
Дистанційна робота
Lviv
Пропозиція дійсна до: 14.06.2026 (залишилося 30 днів)
Вакансія з додатк. підтримкою біженців
Працодавець надає додаткові бенефіти для підтримки біженців у зв’язку з ситуацією в Україні, враховуючи один або декілька з наступних варіантів:
співбесіди українською,
прискорений процес рекрутації,
релокаційний пакет,
психологічна підтримка,
будь-який інший варіант, залежно від роботодавця та кандидата
Необхідні знання
Python
NLP
RESTful
LLM
SQL
NoSQL
pandas
NumPy
ETL
Data analysis
Англійська
(C1)
Буде плюсом
AWS ML stack
Pinecone
Elasticsearch
pgvector
FAISS
DeepLake
GitHub
Наші вимоги
Оригінальний текст.
Показати переклад
3+ years of professional experience researching and shipping ML-based solutions, with strong Python skills and a track record of delivering fast without sacrificing quality
Proven experience in owning research problems end-to-end, starting from initial data analysis, through iterative research phases to delivering on production
Practical NLP/LLM experience: transformers, embeddings, prompt design, and evaluation; ability to choose and justify metrics and methodologies
Strong backend fundamentals: designing RESTful services, schema design, data modeling, and performance tuning for SQL and NoSQL stores
Data processing skills: pandas/NumPy; experience with batch/stream processing and ETL orchestration (e.g., Airflow, Step Functions)
Strong English verbal and written communication
As a plus
LLM ops and safety: eval frameworks (e.g., RAGAS), guardrails, red-teaming, prompt optimization at scale
Model optimization: quantization, distillation, pruning; GPU/accelerator-aware serving
Experience with AWS ML stack (SageMaker, Batch, Step Functions, Lambda, SQS/SNS, DynamoDB, ECS, EC2, S3)
Vector databases and search: Pinecone, Elasticsearch, pgvector, FAISS, or DeepLake
Background in reinforcement learning, agent frameworks, or autonomous agents
Publications, open-source contributions, GitHub portfolio
Про посаду / проект
Оригінальний текст.
Показати переклад
The R&D department plays a pivotal role in driving Shelf to disrupt the market. We are looking for Machine Learning experts that are able to deliver end to end with a blend of experience: Python engineering, ML engineering, and pragmatic Data science and Machine learning research. You will ship end-to-end features—from problem framing and experimentation to service deployment, and ongoing operations—quickly and with high quality. Your work will power ML- and LLM-driven services used by top enterprises like Amazon, Mayo Clinic, AmFam, and Nespresso.
This role requires strong Python engineering capabilities coupled with a strong ability to deliver robust ML solutions, along with ML research literacy to choose sound methodologies, define metrics, and evaluate different approaches effectively.
You’ll work in an agile environment, move fast, and own what you ship.
What Shelf Offers
B2B contract
Company Stock Options
Hardware: MacBook Pro
Modern technical stack. Develop open-source software
Premier AI development environment: GitHub Copilot, Claude Code, OpenAI, TypingMind, v0, MCP Servers, plus credits to experiment with emerging AI tools
About Shelf
There is no AI Strategy without a Data Strategy. Getting GenAI to work is mission-critical for most companies, but 90% of AI projects haven't deployed. Why? Poor data quality—it’s the #1 obstacle companies face getting GenAI into production.
Shelf unlocks AI readiness. We provide the core infrastructure that enables GenAI to be deployed at scale. We help companies deliver more accurate GenAI answers by eliminating bad data in documents and files before they go into an LLM and create bad answers.
We’re partnered with Microsoft, Salesforce, Snowflake, Databricks, OpenAI and other leaders bringing GenAI to the enterprise. Our mission is to empower humanity with better answers everywhere.
Обов'язки
Оригінальний текст.
Показати переклад
Own end-to-end delivery: ideate, research, prototype, productionize, and operate ML-powered services with an expectation to iterate and ship frequently
Stand up robust training/evaluation pipelines: dataset curation, labeling/feedback loops, experiment tracking, offline/online metrics, and A/B testing
Solve problems using sound methodology, evaluate approaches along with
Transform ML models and LLM workflows (including RAG) into reusable, versioned, observable production services with CI/CD
Collaborate with Product Owners to shape our product and requirements
Conduct and receive code reviews; champion engineering excellence, testing discipline, and documentation
показати все
(8)
Деталі
Онлайн-співбесіди
Мова для рекрутингу: українська&англійська
Старт ASAP
Оплачувана відпустка за: B2B
Повністю дистанційна
Гнучкий робочий час
Етапи процесу рекрутингу
0. Intro Call with a recruiter;
1. Tech Screen with a Director of AI
2. Tech Interviews
3. Final Interview
Обладнання
Apple
Комп'ютер: Notebook
Бонуси в офісі
Безоплатна кава
Відсутність дрес-коду
Переваги
Stock options
GitHub Copilot subscription
LLM credits
Невеликі команди
Міжнародні проєкти
Про компанію
Shelf
Transform business operations with agentic AI. An end-to-end system for designing and scaling AI agents.
Заснована в:
2016
Розмір компанії:
50 - 249
Місцезнаходження:
Wrocław + 1
The enterprise is going agentic — but most AI agents fail when they hit real business complexity. Shelf is changing that.
We’ve built the operating system for agentic AI: a platform that models your policies, workflows, and operational logic into an AI Data Model so agents don’t just respond — they reason. The result? AI that understands how your business actually runs and delivers precise, compliant, auditable outcomes at scale.
Brands like Amazon, Nespresso, HelloFresh, and KeyBank trust Shelf to power AI agents that resolve 85% of cases autonomously, cut handle times by 20–25%, and turn hours-long processes into seconds. We’re partnered with Microsoft, Salesforce, OpenAI, Snowflake, and Databricks — and recognized by Gartner (Cool Vendor) and IDC (Innovator) for our approach.
If you want to sell the infrastructure that makes agentic AI actually work in the enterprise, you’re in the right place.
Our mission
is to empower humanity with better answers everywhere.
X XXX - XX XXX PLN
Перевірте, чи є у вас зарплатний метч
> 10k UAH
> 12.5k UAH
> 15k UAH
> 18k UAH
> 20k UAH
> 25k UAH
> 30k UAH
> 40k UAH
> 45k UAH
> 50k UAH
> 55k UAH
> 60k UAH
> 65k UAH
> 70k UAH
> 75k UAH
> 80k UAH
> 85k UAH
> 90k UAH
> 95k UAH
> 100k UAH
> 120k UAH
> 150k UAH
> 170k UAH
> 200k UAH
> 250k UAH
> 270k UAH
> 300k UAH
> 350k UAH
> 370k UAH
> 400k UAH
Діапазон заробітної плати розкриють на першій співбесіді.
Як це працює
Відгукнись
Зберегти вакансію
Налаштувати резюме
BETA