About Fusemachines
Fusemachines is a 10+ year old AI company, dedicated to delivering state-of-the-art AI products and solutions to a diverse range of industries. Founded by Sameer Maskey, Ph.D., an Adjunct Associate Professor at Columbia University, our company is on a steadfast mission to democratize AI and harness the power of global AI talent from underserved communities. With a robust presence in four countries and a dedicated team of over 400 full-time employees, we are committed to fostering AI transformation journeys for businesses worldwide. At Fusemachines, we not only bridge the gap between AI advancement and its global impact but also strive to deliver the most advanced technology solutions to the world.
This a full-time role.
About the role:
You will be involved with various data engineering aspects - data collection, cleaning, and preprocessing, to training models and deploying them to production. The ideal candidate will possess strong technical and interpersonal skills, along with certain ML skills. In addition, the candidate will collaborate across multi-functional teams to achieve product milestones as agreed with stakeholders.
Roles and Responsibilities:
- Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress.
- Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability
- Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
- Verifying data quality and ensuring it via data cleaning
- Defining validation strategies
- Defining the preprocessing or feature engineering to be done on a given dataset
- Defining data augmentation pipelines
- Finding available datasets that could be used for training
- Training models and tuning their hyperparameters
- Analyzing the errors of the model and designing strategies to overcome them
- Deploying models to production
- Work independently and collaboratively on a multi-disciplined project team in an Agile development environment.
- Be actively involved in the design, development and testing activities for Big data product.
- Provide feedback to development teams on code/architecture optimization.
Required Skills and Experience:
- Hands-on experience developing Python, PySpark
- Experience with Spark is preferred
- Possess a strong foundation in statistics and utilize statistical methods to analyze data and derive meaningful insights
- Familiarity with Azure Databricks or similar
- Proficiency with a deep learning frameworks such as TensorFlow or PyTorch or Keras
- Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas
- Expertise in visualizing and manipulating big datasets.
- Ability to select hardware to run an ML model with the required latency
- Familiarity with Azure services
- Proven experience with CI/CD
- Proven experience with version control ( Github, Bitbucket).
- Familiarity with Linux OS/concepts
- Strong written and verbal communication skills
- Self-motivated and ability to work well in a team
Education
Bachelor of Science degree from an accredited university
