Job Title: Machine Learning Engineer/Software Developer

Job Description:
We are seeking a highly skilled and experienced Machine Learning engineer/software developer with a strong background in data science. The ideal candidate will have a minimum of 5 years of experience in machine learning and be an expert in Python programming.

Responsibilities:
1. Designing and developing machine learning systems and predictive models.
2. Running machine learning tests and experiments.
3. Implementing appropriate ML algorithms.
4. Studying and transforming data science prototypes.
5. Selecting appropriate datasets and data representation methods.
6. Performing statistical analysis and fine-tuning using test results.
7. Build, deploy, and optimize machine learning models for predictive analytics, risk assessment, operational improvements and into production.
8. Design, develop, and maintain scalable data pipelines, ETL processes, and data infrastructure, with a focus on Databricks for data processing and analytics.
9. Drive code reviews to ensure code quality, maintainability, and adherence to coding standards.
10. Extending existing ML libraries and frameworks.
11. Keeping abreast of developments in the field.

Requirements:
1. Proven experience as a Machine Learning Engineer or similar role with a minimum of 5 years of experience in machine learning.
2. Minimum of 5+ years of experience in programming with Python.
3. Understanding of data structures, data modeling and software architecture.
4. Strong understanding of machine learning techniques and algorithms, data mining, and statistical analysis.
5. Proficiency with SQL,TensorFlow, PyTorch, Pandas, Keras and related libraries
6. Experience with cloud platform: Azure and Databrick.
7. Strong analytical, problem-solving, and communication skills.
8. Ability to work as part of a team and independently.
9. Outstanding analytical and problem-solving skills.
10. BS in Computer Science, Mathematics, Statistics, or similar field; Master’s degree is a plus.

Pre-Screening Questions:
1. What is the largest data set you have ever analyzed?
a. How many columns and how many rows did that data set have?
2. What type of supervised and unsupervised models have you had experience with? How many years of experience with each?
3. How many years of experience do you have with anomaly detection?
4. How many years of experience with NLP? ChatGPT?
5. Would you describe yourself as an intermediate or expert in statistical methods?
6. How many AI projects have you been involved from development to automation enablement?
7. How many years of experience do you have in maintaining models’ performance after enablement?
8. How many years of experience do you have in building AI agent?
9. What type of AI agents had you build?