Location: India, US, Canada (Vancouver/Toronto)
Flexday invites AI/Machine Learning/ NLP researchers, hobbyists and thought leaders to join our research and development team.
We are seeking a data scientist who is skilled and interested in developing cutting-edge AI-driven solutions for real-world problems. The ideal candidate will be equally comfortable with theoretical reasoning, software engineering, and collaborating with others. Note that this is not a managerial role, and requires extensive hands-on engineering and data analysis work.
- Own the end-to-end development of ML products: from collecting requirements from business stakeholders to deploying and maintaining production models.
- Contribute to the design of highly scalable machine learning (ML) workflows that comply with software engineering best practices.
- Contribute to improving the quality of existing ML products.
- Communicate with business stakeholders and technical teams, and write and maintain documents for different kinds of audiences.
- Collaborate with other data scientists and ML engineers.
- Supervise interns, including planning and regular guidance.
- Keep up to date with the latest ML research and technical skills.
- Be able to deliver and iterate within constrained timeframes.
- Be comfortable communicating regularly while working remotely in a distributed team.
- Excellent knowledge of ML, especially Natural Language Processing (NLP) or computer vision.
- Strong knowledge (at least 5 years) of Python.
- Strong knowledge (at least 3 years) of ML frameworks and libraries, particularly, PyTorch and scikit-learn.
- Good knowledge of ML Ops processes and technologies.
- Good knowledge of cloud infrastructures such as Azure, AWS, or GCP.
- Good knowledge of *nix systems, including working with *nix commands.
- Basic knowledge of working with relational databases and SQL.
- Experience with performance-driven design.
- Excellent verbal and written English communication skills.
- Masters or PhD in a quantitative discipline.
NB: Flexday promotes a flexible work model supporting a blend of in-office, remote, and on-the-go work styles as per employee convenience.