Ar Follow up

Core Responsibilities:

• 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 to deep learning along with employing LLMs in modern frameworks.
• Data Preparation: Prepare, cleanse, and transform data for model training and evaluation.
• Algorithm Implementation: Implement and optimize machine learning algorithms and statistical models.
• System Integration: Integrate models into existing systems and workflows.
• Model Deployment: Deploy models to production environments and monitor performance.
• Collaboration: Work closely with data scientists, software engineers, and other stakeholders.
• Continuous Improvement: Identify areas for improvement in model performance and systems.

Skills:

• Programming and Software Engineering: Knowledge of software engineering best practices (version control, testing, CI/CD).
• Data Engineering: Ability to handle data pipelines, data cleaning, and feature engineering. Proficiency in SQL for data manipulation + Kafka, Chaossearch logs, etc for troubleshooting; Other tech touch points are ScyllaDB (like BigTable), OpenSearch, Neo4J graph
• Model Deployment and Monitoring: MLOps Experience in deploying ML models to production environments.
• Knowledge of model monitoring and performance evaluation.

Required experience:

• Amazon SageMaker: Deep understanding of SageMaker's capabilities for building, training, and deploying ML models; understanding of the Sagemaker pipeline with ability to analyze gaps and recommend/implement improvements
• AWS Cloud Infrastructure: Familiarity with S3, EC2, Lambda and using these services in ML workflows
• AWS data: Redshift, Glue
• Containerization and Orchestration: Understanding of Docker and Kubernetes, and their implementation within AWS (EKS, ECS)

Skills: Aws, Aws Cloud, Amazon Redshift, Eks

Must-Haves

Amazon SageMaker, AWS Cloud Infrastructure (S3, EC2, Lambda), Docker and Kubernetes (EKS, ECS), SQL, AWS data (Redshift, Glue)

Skills : Machine Learning, MLOps, AWS Cloud, Redshift OR Glue, Kubernetes, Sage maker

******

Notice period - 0 to 15 days only 

Location : Pune & Hyderabad only

Job Title: Data Entry Operator / Data Entry Clerk

Job Summary:

Graniti Vicentia India Pvt Ltd is seeking a talented and motivated Data Entry Operator who is

responsible for accurately entering, updating, and maintaining data in company databases and

systems. This role ensures information is recorded efficiently, securely, and with attention to detail

to support smooth business operations

Job Responsibilities:

• Enter and update data into databases, spreadsheets, and systems with high accuracy.

• Verify and correct data to ensure consistency and eliminate errors.

• Review source documents for completeness and clarity before entry.

• Maintain records of activities and completed work.

• Retrieve, organize, and present data for internal reports as required.

• Identify and report discrepancies or data quality issues to supervisors.

Requirements:

• High school diploma or equivalent

• Proven experience in data entry, clerical, or administrative work.

• Strong typing skills with accuracy and speed.

• Proficiency with MS Office (Excel, Word) and database software.

• Good time management skills.

• Strong attention to detail.

• Ability to work independently and meet deadlines.

# Hiring

We are looking for a Lead react Js developer

Hands-on knowledge of UI Development, Rest API, JavaScript, React js, etc

Notice period - Immediate joiner /15 Days

Qualification: B.Tech / MCA / M.Tech

Experience: 4 years- 8 years

Location: Pune / on-site

• Python developer with Django experience
• 6-8 yrs of total experience
• Strong communication is a MUST