Senior Data Scientist (AI Platform)

Munkaidő, foglalkoztatás jellege
- Alkalmazotti jogviszony
- Általános munkarend
Elvárt technológiák
- PYTHON CLOUD DATABASES MACHINE LEARNING BACKEND CI DEBUGGING TESTING
Elvárások
- Angol középfok
- 5-10 év tapasztalat
- Középiskola

Állás elmentve

A hirdetést eltávolítottuk a mentett állásai közül.

Architect, build, and operate scalable inference services, APIs, and backend components for model-driven and LLM-powered product features
Productionize AI and ML workflows with strong MLOps practices including model versioning, testing, deployment pipelines, monitoring, rollback, and operational reliability
Define and implement evaluation frameworks for model quality, system reliability, latency, and cost
Build reusable platform patterns, service templates, and reference implementations for multiple teams and products
Set and uphold engineering standards across the AI team including code quality, documentation, observability, and incident readiness
Mentor team members in production ML practices
Partner with infrastructure owner on cloud, cluster, and CI substrate and with product, engineering, and research partners to move AI capabilities into production

6+ years of experience in software engineering, machine learning engineering, or applied AI engineering with clear ownership of systems in production
Experience taking ML and LLM systems from prototype to production and operating them in live environments
Strong experience building and operating APIs and services (Python preferred)
Experience working with containers
Experience debugging reliability and performance issues in production
Strong MLOps skills including deployment and orchestration pipelines, model and artifact versioning, monitoring, and rollback for ML and LLM workloads
Working knowledge of modern AI patterns such as embeddings, retrieval, semantic search, and RAG and their production constraints

Experience with vector databases, retrieval infrastructure, or semantic indexing pipelines
Experience with graph databases or graph-based reasoning systems
Experience with observability and evaluation for LLM or retrieval systems including quality metrics, drift, and failure analysis
Track record of internal engineering standards, templates, or reference implementations adopted by multiple teams
Experience mentoring engineers in a high-growth or platform-building environment
Experience in edtech, learning systems, or knowledge and skills modeling

Competitive compensation
Participation in ownership program for full-time employees
Flexible work culture with remote, hybrid, and in-office collaboration spaces
Generous time off including local holidays and annual “Dim the Lights” period
Comprehensive wellness programs and mental health support
Learning and development resources including professional development tools and tuition reimbursement
Technology and tools needed to do best work
Motivosity employee recognition program
Culture rooted in inclusivity, support, and meaningful connection