Senior Machine Learning Engineer - Bluevineisrael

Build AI/ML Infrastructure: Design, develop, and maintain platforms and tooling that accelerate the entire AI lifecycle-from experimentation and training to deployment, observability, and governance. Productionize AI: Partner with our Data Science, Analytics, and Research teams to turn prototypes and notebooks into highly reliable, scalable production systems. Develop Modern AI Workflows: Build robust data and feature pipelines, and develop reusable components for GenAI capabilities like LLMs, embeddings, RAG, and agentic workflows. Champion Best Practices: Utilize orchestration tools, cloud AI services (such as AWS Bedrock, SageMaker, etc.), and modern frameworks to design first-in-class solutions for the financial sector. 5+ years of full-time Software Engineering experience in a fast-paced, data-centric environment, with strong proficiency in Python. 2+ years of hands-on experience in a Machine Learning Engineering, MLOps, ML Infrastructure, or hands-on, full-stack Data Science role. Deep understanding of the entire ML/DS lifecycle, from research and development to deployment. Proven hands-on experience in building production-grade solutions, platforms, or infrastructure for AI or ML. Experience building and deploying modern AI and LLM-based systems (prompt orchestration, embeddings, retrieval-augmented generation, and evaluation frameworks). Deep experience with cloud infrastructure (AWS preferred), including services like SageMaker, Bedrock, Lambda, and S3. Strong software engineering fundamentals, including system design, CI/CD, testing, code quality, and operational excellence. Exceptional communication skills, with the ability to collaborate smoothly and explain complex technical ideas clearly. Proactive, result-driven team player with very good English (written and verbal). Experience with vector databases, advanced experiment tracking tools, or 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. Excellent group health coverage Stock options Flexible hybrid work model Large Study Fund contribution Salary Benchmarks and Checkpoints Monthly meal card of TenBis or CiBus (your choice) with generous balance Free parking for cars, scooters, and bikes Free gym membership Company-sponsored Mental Health Benefits PTO, Company Holidays, and Flexible Holidays Community-based volunteering opportunities

At Bluevine, we’re on a mission to empower small businesses with innovative financial solutions. In this role, you will take an integral part in designing the next-generation infrastructure that powers our data-driven products. You will help shape and build the platforms and production-grade solutions that enable our Data teams to deliver impactful AI/ML capabilities at scale. If you are passionate about turning complex data into reliable, scalable systems that solve real-world financial challenges, we want you on our team.

Build AI/ML Infrastructure: Design, develop, and maintain platforms and tooling that accelerate the entire AI lifecycle-from experimentation and training to deployment, observability, and governance. Productionize AI: Partner with our Data Science, Analytics, and Research teams to turn prototypes and notebooks into highly reliable, scalable production systems. Develop Modern AI Workflows: Build robust data and feature pipelines, and develop reusable components for GenAI capabilities like LLMs, embeddings, RAG, and agentic workflows. Champion Best Practices: Utilize orchestration tools, cloud AI services (such as AWS Bedrock, SageMaker, etc.), and modern frameworks to design first-in-class solutions for the financial sector. 5+ years of full-time Software Engineering experience in a fast-paced, data-centric environment, with strong proficiency in Python. 2+ years of hands-on experience in a Machine Learning Engineering, MLOps, ML Infrastructure, or hands-on, full-stack Data Science role. Deep understanding of the entire ML/DS lifecycle, from research and development to deployment. Proven hands-on experience in building production-grade solutions, platforms, or infrastructure for AI or ML. Experience building and deploying modern AI and LLM-based systems (prompt orchestration, embeddings, retrieval-augmented generation, and evaluation frameworks). Deep experience with cloud infrastructure (AWS preferred), including services like SageMaker, Bedrock, Lambda, and S3. Strong software engineering fundamentals, including system design, CI/CD, testing, code quality, and operational excellence. Exceptional communication skills, with the ability to collaborate smoothly and explain complex technical ideas clearly. Proactive, result-driven team player with very good English (written and verbal). Experience with vector databases, advanced experiment tracking tools, or 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. Excellent group health coverage Stock options Flexible hybrid work model Large Study Fund contribution Salary Benchmarks and Checkpoints Monthly meal card of TenBis or CiBus (your choice) with generous balance Free parking for cars, scooters, and bikes Free gym membership Company-sponsored Mental Health Benefits PTO, Company Holidays, and Flexible Holidays Community-based volunteering opportunities