- Machine Learning Recruiters and Staffing SpecialistsApplied Scientist
Machine Learning Jobs
- AI/ML Engineer
- Applied Scientist
- Computer Vision Engineer
- Computer Vision Research Scientist
- Generative AI Engineer
- Large Language Model (LLM) Engineer
- Lead Machine Learning Engineer
- Machine Learning Architect
- Machine Learning Infrastructure Engineer
- Machine Learning Platform Engineer
- Machine Learning Research Scientist
- ML Product Manager
- MLOps Engineer
- Natural Language Processing (NLP) Engineer
- Principal Machine Learning Engineer
- Recommendation Systems Engineer
- Research Engineer
- Senior Machine Learning Engineer
- VP of Machine Learning
The applied scientist sits between research and engineering, taking methods that work in principle and making them work on the organization’s actual problem and data. The role requires research training and enough engineering to ship, and it is judged on measurable improvement to a product or process rather than on publications.
Typical Duties and Responsibilities
- Apply and adapt research methods to specific business problems
- Design experiments and evaluation tied to real outcomes
- Build models and validate them against production conditions
- Work with engineers to deploy and monitor solutions
- Analyze data to identify where modeling can help and where it cannot
- Run online experiments and interpret the results correctly
- Communicate findings and their uncertainty to stakeholders
- Maintain reproducible experimental code
- Review literature relevant to the organization’s problems
- Mentor colleagues on scientific method and evaluation
Education
- PhD or Master’s in a quantitative discipline
Required Skills and Experience
- 3+ years applying scientific methods to production problems
- Strong statistics and experimental design
- Proficiency with Python and machine learning frameworks
- Ability to connect modeling work to measurable business outcomes
- Experience with online experimentation and its pitfalls
- Software engineering competence sufficient to ship
- Clear communication of uncertainty
- Willingness to conclude that modeling is not the answer
Preferred Qualifications
- Publications or conference presentations
- Domain experience relevant to the organization