Machine Learning/ai Engineer

hace 5 días

Buenos Aires, Argentina Backoffice Abroad A tiempo completo

Backoffice Abroad is a young, fast-growing company that strives to provide high-quality outsourcing services to US-based clients. Backoffice Abroad was founded by a lawyer and a business administrator, looking to harness their expertise and relevant local experiences to ensure that demanding employers can find high-quality, yet affordable workers to join their ranks.

**Responsibilities**
- Designing, developing, and maintaining machine learning systems.
- Consulting with managers and stakeholders to determine machine learning objectives.
- Researching and experimenting with new, suitable machine learning algorithms and tools.
- Developing machine learning algorithms to analyze large data sets and make future predictions.
- Designing machine learning systems, as well as artificial intelligence software to automate certain predictive models and tasks.
- Extending and enriching machine learning frameworks and libraries.
- Optimizing existing machine learning libraries and frameworks.
- Testing, performing analysis, and interpreting the results for future improvements.
- Keeping documentation of the machine learning process.
- Staying up to date with machine learning developments across the industry

**Requirements**:

- Degree in Machine Learning, Artificial Intelligence, Data Science, Mathematics, or a similar field.
- At least 2 years of experience working as a Machine Learning Engineer.
- Proficiency in Python, Java, R and C++.
- Skilled in using big data frameworks such as Hadoop, Spark, Pig, Hive etc.
- Experience working with machine learning frameworks like Theano, Tensorflow, Caffe, etc.
- Extensive and deep knowledge of Machine Learning practices, libraries, data structures, and software architecture.
- A passion for statistics and mathematics, with good communication skills to be able to explain complex ideas and concepts into easy-to-understand conversations.
- Outstanding problem-solving skills with an analytical approach to work.

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