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DigiHelic Solutions Pvt. Ltd.
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Job Description
Job Role: ML EngineerExperience: 6-12 YearsLocation: Pune, Bangalore, Hyderabad, Trivandrum, Chennai, Kochi, Gurgaon, NoidaKey Summary:● The MLE will design, build, test, and deploy scalable machine learning systems,optimizing model accuracy and efficiency● Model Development: Algorithms and architectures span traditional statistical methods todeep learning along with employing LLMs in modern frameworks.● Data Preparation: Prepare, cleanse, and transform data for model training andevaluation.● Algorithm Implementation: Implement and optimize machine learning algorithms andstatistical models.● System Integration: Integrate models into existing systems and workflows.● Model Deployment: Deploy models to production environments and monitorperformance.● Collaboration: Work closely with data scientists, software engineers, and otherstakeholders.● Continuous Improvement: Identify areas for improvement in model performance andsystems.Skills:● Programming and Software Engineering: Knowledge of software engineering bestpractices (version control, testing, CI/CD).● Data Engineering: Ability to handle data pipelines, data cleaning, and featureengineering.
Proficiency in SQL for data manipulation + Kafka, Chaossearch logs, etc fortroubleshooting; Other tech touch points are Scylla DB (like Big Table), Open Search,Neo4 J graph● Model Deployment and Monitoring: MLOps Experience in deploying ML models toproduction environments.● Knowledge of model monitoring and performance evaluation.Required experience:● Amazon Sage Maker: Deep understanding of Sage Maker's capabilities for building,training, and deploying ML models; understanding of the Sagemaker pipeline with abilityto analyze gaps and recommend/implement improvements● AWS Cloud Infrastructure: Familiarity with S3, EC2, Lambda and using these services inML workflows● AWS data: Redshift, Glue● Containerization and Orchestration: Understanding of Docker and Kubernetes, and theirimplementation within AWS (EKS, ECS)Skills:Aws, Aws Cloud, Amazon Redshift, Eks
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