ML Engineer
ML Engineer
Posted on :
09-03-2025
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1 Vacancy
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Job Description
Position: Machine Learning Engineer
Location: Mumbai
Experience Level: 3 Years
About the Role Weare seeking a highly skilled and innovative Machine Learning Engineer to join our team. You will design develop and deploy cuttingedge ML solutions to solve realworld 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. Workclosely 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 largescale 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. Workwith crossfunctional teams to interpret data identify trends and implement datadriven strategies.
Qualifications:
Education: Bachelors or Masters 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 Scikitlearn 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 problemsolving and analytical thinking skills.
Familiarity with AWS services (S3 Redshift SageMaker Lambda etc. is an advantage.
Familiarity with A/B testing and experimentation frameworks.
Employment Type
Full Time
Key Skills
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