UST transforms lives through the power of technology by embedding innovation and agility into everything they do, helping clients create transformative experiences and human-centered solutions for a better world. The Machine Learning Engineer will develop, test, and deploy machine learning models that solve real business problems using state-of-the-art techniques.
Requirements
- Strong understanding of the machine learning model building lifecycle.
- Knowledge of various ML techniques and when to apply them to business problems.
- Solid foundation in statistics and mathematics.
- Domain expertise in one of the following: Computer Vision, Natural Language Understanding, Structured Data & Tabular ML
- Experience with data wrangling, preprocessing, and post-processing techniques.
- Proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Caffe.
- Familiarity with machine learning model testing and validation approaches.
Responsibilities
- Perform data wrangling and preprocessing to create high-quality datasets.
- Conduct ML experiments to evaluate feasibility and create baseline models.
- Fine-tune baseline models to achieve optimum performance.
- Test ML models based on acceptance criteria defined by business stakeholders.
- Document experiments, models, and technical artifacts for business and engineering teams.
- Work with data scientists and ML engineers to deploy models into production.
- Collaborate with product teams in planning and executing new product releases.
Other
- 3+ years of experience
- Ability to work collaboratively with engineering, design, product, and business teams.
- Strong documentation, communication, and analytical skills.
- Curiosity, adaptability, and a continuous learning mindset.
- Set OKRs, track progress, and contribute to team goals.
