Machine Learning Engineer

3 weeks ago

Mumbai, Maharashtra, India Discoveries Quintessential Full time

Position: Machine Learning Engineer Location: Mumbai Experience: 3+ Years About the Role We are seeking a highly skilled and innovative Machine Learning Engineer to join the team. You will design, develop, and deploy cutting-edge ML solutions to solve real-world problems, driving impactful outcomes for our organization. Collaborating closely with software engineers, and product teams, you will build scalable and efficient ML models and pipelines. Key Responsibilities: 1. Machine Learning Model Development and Deployment: ○ Design, build, and optimize machine learning models to solve business problems. ○ Deploy trained models to production environments using MLOps practices (e.g., CI/CD pipelines, model versioning, and monitoring), ensuring scalability, reliability, and efficiency. ○ Continuously monitor model performance and implement improvements to maintain and enhance accuracy. ○ Implement and optimize feature engineering workflows, including working with feature stores. 2. Business Impact Through ML: ○ Leverage ML solutions to improve core business KPIs, including transaction success rates, fraud detection, customer retention, and operational efficiency. ○ Work closely with business stakeholders to identify ML use cases aligned with organizational goals. 3. Data Engineering and ETL Processes: ○ Design and implement ETL pipelines for efficient data extraction, transformation, and loading. ○ Collaborate with data engineers to maintain a robust data pipeline connecting OLTP and OLAP systems. 4. Data Warehouse Expertise: ○ Utilize AWS Redshift to manage and analyze large-scale datasets. ○ Develop and optimize queries for reporting and feeding ML models. 5. Analytical Problem Solving: ○ Apply strong analytical skills to derive insights from data and translate them into actionable recommendations. ○ Work with cross-functional teams to interpret data, identify trends, and implement data-driven strategies. Qualifications: ● Education: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field. ● Experience: ○ Proven experience in training, deploying, and maintaining ML models in production. ○ Proficiency in ML libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn etc.). ○ Experience with cloud platforms like AWS, Azure, or GCP, especially for ML workloads. ○ Knowledge of data preprocessing, feature engineering, data warehousing (ie. Redshift) and ETL pipelines. ○ Familiarity with MLOps tools and practices (e.g., Docker, Kubernetes, MLflow, Sagemaker) would be a plus. ○ Strong understanding of statistical methods, algorithms, and performance optimization. ○ Experience in the fintech domain is a plus. ● Skills: ○ Proficiency in SQL for data analysis and manipulation. ○ Strong problem-solving and analytical thinking skills. ○ Familiarity with AWS services (S3, Redshift, SageMaker, Lambda, etc.) is an advantage. ○ Familiarity with A/B testing and experimentation frameworks.

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