- Azure
- AWS
- MLOps
- machine learning models in production environment
STUDYMONT FUTURE TECHNOLOGIES PRIVATE LIMITED This company domain is unverified.
India
Job Title
Machine Learning Model Trial Testing Specialist
Experience
Senior
Vacancies
300
Salary
1000 Hourly
Office time
N/A
Location
Anywhere
Job Type
Freelance Remote
Deadline
30 November, 2024
Skills
Description
Job Description: We are seeking a highly skilled Machine Learning Model Trial Testing Specialist to evaluate and optimize our machine learning models. The ideal candidate will have a strong background in machine learning, data analysis, and testing methodologies. You will be responsible for conducting rigorous trials of our models, ensuring their accuracy and effectiveness in real-world applications.
Qualifications:
- Proven experience in machine learning model testing and evaluation.
- Proficiency in programming languages such as Python, R, or Java.
- Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Strong understanding of statistical analysis and data visualization techniques.
- Experience with version control systems (e.g., Git) and agile development methodologies.
- Excellent problem-solving skills and attention to detail.
- Strong communication skills, both verbal and written.
Preferred Qualifications:
- Experience in deploying machine learning models in production environments.
- Knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud) and their machine learning services.
- Familiarity with MLOps practices and tools.
Job Responsibilities
Key Responsibilities:
- Design and implement test plans for machine learning models.
- Conduct thorough testing to evaluate model performance, accuracy, and robustness.
- Analyze test results and provide actionable insights for model improvement.
- Collaborate with data scientists and engineers to optimize model parameters and features.
- Develop and maintain documentation of testing processes and outcomes.
- Stay updated on the latest advancements in machine learning and testing methodologies.
- Communicate findings and recommendations to stakeholders effectively.