About this AI/ML Engineer role at Weekday AI
๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ฎ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ฏ๐ด๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ฎ๐ฌ-๐ฏ๐ด ๐๐ฃ๐)
Experience: 6+ yrs
Location: Pune, Maharashtra, India
Job Type: Full-time
We are looking for an experiencedย AI/ML Engineerย with 6+ years of experience inย Data Science, Machine Learning, and Pythonย to design, develop, and deploy intelligent, data-driven solutions. The role requires strong expertise in machine learning algorithms, statistical analysis, data processing, model development, and productionisation of AI/ML solutions.
The ideal candidate will combine strongย Data Scientistย capabilities with hands-on engineering skills to solve complex business problems using data. You will work across the machine learning lifecycle, from data exploration and feature engineering through model development, evaluation, deployment, monitoring, and continuous improvement.
Requirements
Key Responsibilities
- Design, develop, test, and deployย Machine Learningย models for business and product use cases.
- Applyย Data Scienceย techniques to analyze structured and unstructured datasets and identify actionable insights.
- Useย Pythonย extensively for data processing, statistical analysis, feature engineering, model development, and automation.
- Perform exploratory data analysis and identify trends, patterns, anomalies, and relationships within complex datasets.
- Develop and evaluate supervised and unsupervised machine learning models, including classification, regression, clustering, and forecasting techniques.
- Perform feature engineering, feature selection, model tuning, and validation to improve model performance.
- Define appropriate evaluation metrics and establish robust model validation and experimentation practices.
- Translate business problems into analytical and machine learning problems with clear objectives and measurable outcomes.
- Build reusable data and machine learning pipelines to support experimentation and production deployment.
- Collaborate with Data Engineers to prepare reliable datasets and scalable data-processing workflows.
- Work with software engineers to integrate machine learning models into production applications and services.
- Monitor deployed models and identify opportunities for performance, accuracy, and reliability improvements.
- Conduct experiments, document findings, and communicate analytical results to technical and non-technical stakeholders.
- Implement appropriate practices for data quality, model governance, reproducibility, and documentation.
- Stay current with emergingย AI, Machine Learning, Data Science, and Pythonย technologies and industry practices.
What Makes You a Great Fit
- 6+ years of professional experienceย inย Data Science, Machine Learning, AI/ML Engineering, or a closely related field.
- Strong hands-on expertise inย Pythonย for data analysis, machine learning, automation, and production development.
- Strong understanding ofย Machine Learning algorithms, statistical methods, model evaluation, and predictive analytics.
- Proven experience developing, tuning, validating, and deploying machine learning models.
- Strong Data Science fundamentals, includingย EDA, feature engineering, data preprocessing, experimentation, and statistical analysis.
- Experience with Python libraries such asย Pandas, NumPy, Scikit-learn, and relevant machine learning frameworks.
- Good understanding of supervised and unsupervised learning techniques and their practical applications.
- Experience working with large datasets, data pipelines, and structured or unstructured data.
- Strong SQL skills and experience working with relational or analytical databases.
- Familiarity withย MLOps, model deployment, monitoring, CI/CD, Docker, or cloud platformsย is an advantage.
- Strong analytical and problem-solving skills with the ability to translate complex business requirements into practical ML solutions.
- Excellent communication skills and the ability to present technical findings clearly to diverse stakeholders.
- Strong ownership, attention to detail, and ability to work independently in a fast-paced environment.
- Bachelor's or Master's degree inย Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related disciplineย is preferred.