3 дня назад
Senior Machine Learning Engineer, Foundational Models and Agentic Systems (Generative AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Machine Learning Engineer, Foundational Models and Agentic Systems (Generative AI): Building and deploying generative AI models and end-to-end data pipelines at scale with an accent on inference optimization, quantization, fine-tuning, and evaluation. Focus on designing production-ready AI architectures, improving model performance, and integrating distributed computing and cloud technologies.
Location: Petach Tikva, Israel
Company
is a global financial technology platform powering 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 and build systems for generative AI inference, quantization, optimization, fine-tuning, and evaluation.
- Develop generative AI architectures and production-ready machine learning systems.
- Work with product managers, data scientists, and engineers to design and refine generative AI models.
- Build end-to-end data pipelines and refine features from diverse data sources.
- Explore state-of-the-art technologies and communicate results to peers and leaders.
Requirements
- Experience with LLM tools and frameworks, including LangChain, vLLM, and Hugging Face.
- Proficiency in Python, Spark, and machine learning techniques including classification, regression, clustering, training, validation, and testing.
- Experience with AWS, Docker, Kubernetes, and Kubeflow or MLflow.
- Knowledge of relational and NoSQL data systems, stream processing, Hive, and distributed computing.
- Strong software engineering and computer science fundamentals, including Git, algorithms, data structures, performance, complexity, and computer architecture.
- BS, MS, or PhD in Computer Science or a related field, or equivalent practical experience; knowledge of linear algebra, calculus, and probability.
Culture & Benefits
- Collaboration with data scientists and machine learning engineers across multiple 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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