обновлено 10 дней назад
Senior Machine Learning Engineer (Generative AI)
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Senior Machine Learning Engineer (Generative AI): Building and deploying foundational GenAI models and agentic systems at scale with an accent on inference, quantization, optimization, fine-tuning, and evaluation. Focus on designing production-ready architectures, developing end-to-end data pipelines, and improving model performance through distributed computing and cloud technologies.
Location: Petach Tikva, Israel
Company
is a global financial technology platform serving approximately 100 million customers through products including TurboTax, Credit Karma, QuickBooks, and Mailchimp.
What you will do
- Code, optimize, deploy, monitor, and improve Generative AI models and solutions at scale.
- Design systems for GenAI inference, quantization, optimization, fine-tuning, and evaluation.
- Design and refine Generative AI models and architectures in collaboration with product managers, data scientists, and engineers.
- Work with diverse data sources to refine features and build end-to-end data pipelines.
- Explore state-of-the-art technologies and apply them to deliver customer benefits.
- Communicate technical results to peers and leaders.
Requirements
- Experience with LLM tools and frameworks, including LangChain, vLLM, and Hugging Face.
- Experience with Python, Spark, AWS, Docker, Kubernetes, and Kubeflow or MLflow.
- Experience designing and developing Generative AI architectures.
- Knowledge of machine learning techniques including classification, regression, and clustering, as well as training, validation, and testing principles.
- Experience with relational and NoSQL data systems, stream processing, and distributed technologies such as Spark and Hive.
- Production-ready software engineering skills, including Git/GitHub workflows, data structures, algorithms, performance optimization, and mathematical foundations such as linear algebra, calculus, and probability; BS, MS, or PhD in Computer Science or a related field, or equivalent practical experience.
Culture & Benefits
- Work as part of a team of data scientists and machine learning engineers.
- Collaborate across multiple teams and business units.
- Competitive compensation with performance-based rewards.
- Potential eligibility for cash bonus, equity rewards, and benefits under applicable plans and programs.
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