Offer summary

Qualifications:

Last year of a bachelor’s degree in Computer Science or related field., Proficient in English with basic knowledge of Python, ML, and data libraries., Understanding of statistical, ML, and deep learning algorithms., Experience visualizing and manipulating big datasets..

Key responsabilities:

Assist in designing, developing, and maintaining data pipelines for clean and reliable data.

Collaborate with the team to implement and optimize ETL processes.

Support data management tasks including data cleaning, validation, and transformation.

Participate in client communications to gather requirements and communicate deliverables.

Job description

Duration: Six months

Format: Full time (40 hrs/week), paid

In the last year at Loka, our teams launched almost 200 GenAI projects for companies of all kinds, including the world’s Number 1 GenAI reading tutor, a startup that transforms homes into batteries and a leading cancer-fighting laboratory. And we did it all while enjoying every other Friday off 😎

As a Data Engineering Machine Learning Intern, you'll gain professional experience supporting Loka’s certified specialists, technical experts and PhDs while elevating your skillset, building a portfolio and launching projects you’re proud of.

The Role

Assist in designing, developing and maintaining data pipelines to ensure clean, reliable and timely data.
Collaborate with the team to implement and optimize ETL processes.
Integrate data from various sources into warehouses, data lakes and lakehouses.
Support data management tasks, including data cleaning, validation and transformation.
Understand business objectives and develop models that help achieve them, plus metrics to track their progress.
Implement ML systems using classical ML, DL and Foundation Models following best practices.
Participate in client communications by helping gather requirements and communicate deliverables.
Explore and visualize data with a careful eye for issues that require data cleaning as well as differences in data distribution that may affect performance after deployment.
Identify and analyze model errors.

Required Hard Skills

Last year of a bachelor’s degree in Computer Science or related
Proficient in English
Basic knowledge of Python, ML, and Data libraries
Basic knowledge of Databases
Understanding of statistical, ML ,and deep learning algorithms
Experience visualizing and manipulating big datasets
Problem solving
Bonus: AWS knowledge, (Py)Spark, Airflow, Data Lakes and Data Warehouses

Required Soft Skills

Curiosity: You’re ambitious to learn and grow in different industries utilizing a modern tech stack.
Autonomy and positivity: We’re a fully remote, globally distributed team.
Teamwork: Enjoy a collaborative approach.
Adaptability: Operate with a startup mindset and move at a startup pace.
Dependable: You can be trusted to deliver high-quality work.

Benefits