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Senior Machine Learning Engineer
ГибридПолная занятостьAI & Machine LearningFinancial Services
Join a financial technology platform team building scalable AI/ML infrastructure and production-grade systems. The role covers the full machine learning lifecycle, from experimentation and training through deployment, observability, and governance, with a focus on modern LLM and generative AI use в
Обязанности
- Design and maintain AI/ML infrastructure, platforms, and tooling
- Support experimentation, training, deployment, observability, and governance across the AI lifecycle
- Convert data science prototypes and notebooks into reliable, scalable production systems
- Build data and feature pipelines
- Develop reusable components for LLMs, embeddings, retrieval-augmented generation, and agentic workflows
- Use orchestration tools, cloud AI services, and modern frameworks
- Collaborate with data science, analytics, and research teams
Требования
- 5+ years of full-time software engineering experience in a fast-paced, data-centric environment
- 2+ years of hands-on experience in machine learning engineering, MLOps, ML infrastructure, or full-stack data science
- Strong Python proficiency
- Deep understanding of the machine learning and data science lifecycle
- Hands-on experience building production-grade AI/ML solutions, platforms, or infrastructure
- Experience building and deploying AI and LLM-based systems, including prompt orchestration, embeddings, retrieval-augmented generation, and evaluation frameworks
- Deep experience with cloud infrastructure, preferably AWS, including SageMaker, Bedrock, Lambda, and S3
- Strong software engineering fundamentals in system design, CI/CD, testing, code quality, and operational excellence
- Excellent written and verbal English communication skills
Будет плюсом
- Experience with vector databases
- Experience with advanced experiment tracking tools
- Experience with specialized ML observability platforms
- Background in streaming, event-driven systems, and real-time analytics
- Experience with responsible AI, model risk management, explainability, or bias testing in regulated industries
- Experience in fintech, banking, lending, risk, fraud, or financial data systems
Условия и преимущества
- Excellent group health coverage
- Stock options
- Flexible hybrid work model
- Large Study Fund contribution
- Salary benchmarks and checkpoints
- Monthly meal card
- Free parking for cars, scooters, and bikes
- Free gym membership
- Company-sponsored mental health benefits
- Paid time off, company holidays, and flexible holidays
- Community-based volunteering opportunities