SR DATA SCIENTIST/NLP WITH ENGLISH
Descripción de la oferta de empleo
Working closely with machine learning engineers and software engineers, you will tackle real-world business challenges using advanced machine learning techniques.
Your responsibilities include delivering impactful products that directly influence people’s lives.
Take the next exciting step and be part of our journey to revolutionize the field of human capital management! Main Responsibilities Create and deploy Machine Learning systems utilizing programming languages, frameworks, and tools like Python, AWS, and Databricks Collaborate with engineering and product teams within an Agile environment to discover, design, develop, and implement advanced Machine Learning solutions Builds solutions on top of LLM Demonstrate proficiency in constructing models, specifically in domains such as NLP, deep learning, classification algorithms, or recommender systems Produce impeccable code and documentation, advocate for and establish best practices to generate adaptive, high-performing, and continuously learning AI models and systems Provide guidance and support for the professional development of fellow team members through mentoring Core Skills/experience Hold a bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or an equivalent qualification Possess 3-5 years of experience, honing and developing the relevant skills required for this role, gained through work in a similar or related capacity Have a high level of proficiency in Python, including popular data science packages (Pandas, Sklearn, etc.), a strong knowledge of data structures, algorithms, and methods used for data science and machine learning, and familiarity with natural language processing.
Nice to have.
Experience with AWS cloud solutions like Lambda and SageMaker, as well as expertise in CI/CD tools like Jenkins and non-relational databases (NoSQL) and exposure to platforms like Databricks, MLflow, and Jupyter notebooks
Detalles de la oferta
- Sin especificar
- Sin especificar
- 18/09/2024
- 17/12/2024
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