12 часов назад
Data Scientist / Machine Learning Engineer (Generative AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Scientist / Machine Learning Engineer (Generative AI): Designing, training, and productionizing machine learning and deep learning models, including LLM-driven applications and RAG pipelines, for scalable big-data analytics systems with an accent on Python, PyTorch, model deployment, and MLOps. Focus on fine-tuning LLMs, integrating vector databases, monitoring model drift, and building reliable training and serving workflows with Docker, Kubernetes, and CI/CD.
Location: Remote, based in Latin America; listed locations include Argentina, Brazil, Colombia, Mexico, and the United States
Company
is a San Francisco-based software development firm specializing in AI software development, data, cloud, Generative AI, and custom machine learning solutions.
What you will do
- Design, train, validate, and productionize supervised, unsupervised, and deep learning models for anomaly detection, classification, forecasting, and other analytics use cases.
- Develop and fine-tune large language models and build LLM-driven applications using RAG pipelines and vector databases.
- Build scalable model deployment and data pipelines with Python, pandas, NumPy, Spark, Docker, Kubernetes, and CI/CD.
- Automate model training and serving workflows with Airflow or similar orchestration tools.
- Monitor production model performance, detect drift, and implement retraining and LLMOps practices.
- Collaborate with data engineers, software developers, DevOps, and product owners to align requirements and service-level expectations.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
- At least 5 years of professional experience using Python in production environments.
- Strong machine learning and deep learning background, including CNNs, Transformers, LLMs, and PyTorch.
- Experience deploying machine learning solutions and expertise with pandas, NumPy, and scikit-learn.
- Strong foundation in statistics and experimental design.
- Professional English proficiency at B2/C1 level is required.
Nice to have
- Experience with AWS, GCP, Azure, or AI services such as SageMaker, Vertex AI, or Azure Machine Learning.
- Experience with Spark, Hadoop, CI/CD, Docker, Kubernetes, MLflow, Kubeflow, or TFX.
- Experience with Generative AI, prompt engineering, RAG pipelines, vector databases, AI agents, Hugging Face Transformers, LangChain, or LangGraph.
- Experience documenting architectures and workflows with PlantUML or similar tools.
Culture & Benefits
- Fully remote work with collaboration across a dynamic data and analytics team.
- Paid time off and U.S. holidays.
- Training support and free Udemy Premium access.
- Mentored career development and profit sharing.
- U.S.-dollar remuneration.
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