Machine Learning Engineer

Banani, Dhaka | Machine Learning | Full-time



Therap is a global company that provides information technology services to healthcare professionals serving intellectually and developmentally disabled patient populations. Therap is investigating ways to incorporate networked biometric devices into its service offerings. We are seeking to hire a recently graduated with a degree in computer science or computer engineering to help us assess which commercially available devices are most compatible with the Therap platform.

What you’ll be doing:

  • Research, design, develop, and test various AI/ML frameworks and models
  • Evaluate and classify various AI/ML implementations and map it against applicable use cases
  • Mentor other team members and data analytical groups
  • Take the lead in developing innovative advanced analytical solutions for complex application problems
  • Work independently with minimal supervision and be an advocate for the adoption of data science, AI/ML solutions

What we need to see:

  • Bachelor's in Computer Science or Engineering or a closely related discipline.
  • Strong programming/debugging skills in Python.
  • Good Data Science skills. Processing, cleaning, and visualizing structured/unstructured data using libraries such as Numpy, Pandas, Matplotlib, Seaborn, and SciPy, etc. in a Jupyter notebook environment.
  • Good knowledge of data transformation and/or preparing data suitable for ML algorithms. 
  • Experience in building and deploying Machine Learning solutions using various supervised/unsupervised ML algorithms such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Random Forest, etc.
  • Experience in building and deploying ML models using libraries such as scikit-learn, Keras, and TensorFlow.

Ways to stand out from the crowd:

  • 1+ year of industrial experience with Python
  • 2+ years of experience working in industry solving real world problems using AI
  • M.S. in Computer Science of closely related engineering field
  • Deploying ML models on embedded platforms and/or large scale cloud services (AWS, GCP, Azure)