Physiotherapist

Role Overview:

The Safety Manager will be responsible for implementing and monitoring safety policies at construction sites to ensure compliance with statutory regulations and maintain a safe working environment for all employees and workers.

Key Responsibilities:

Develop and implement site safety policies and procedures.

Conduct regular safety inspections and risk assessments.

Ensure compliance with MBOCW/BOCW rules and other statutory safety regulations.

Investigate accidents, incidents, and near-miss cases and recommend corrective actions.

Conduct safety training programs and toolbox talks for workers and staff.

Monitor the use of PPE and ensure safety standards are followed on-site.

Maintain safety records, reports, and compliance documentation.

Coordinate with project managers and site teams to implement safety measures.

Identify potential hazards and implement preventive actions.

Ensure emergency response and safety preparedness at the construction site.

Qualifications:

Degree/Diploma in Engineering or Science.

Advanced Diploma in Industrial Safety (CLI/RLI/State Board approved)

OR Diploma in Construction Safety Management from NICMAR.

Experience Required:

Minimum 8–15 years of experience in construction safety management.

About the job

Job Title: MLOps Engineer Intern

Company: Aaizel International Technologies Pvt. Ltd.

Location: Gurugram, Haryana (On-site)

Duration: 6 Months (PPO based on performance)

About Aaizeltech

Aaizeltech is a deep-tech company building AI/ML-powered platforms, scalable SaaS applications, cybersecurity solutions, and intelligent embedded systems. We are looking for a passionate MLOps Engineer Intern eager to work on real-world machine learning infrastructure, cloud platforms, and deployment pipelines while collaborating with experienced AI/ML engineers.

Role Overview

As an MLOps Engineer Intern, you will assist in building, deploying, and maintaining machine learning pipelines and cloud infrastructure. You will gain hands-on experience in containerization, Kubernetes, CI/CD automation, model deployment, monitoring, and cloud-native technologies while contributing to production-ready AI solutions.

Key ResponsibilitiesMLOps

• Assist in building and maintaining end-to-end ML pipelines using tools such as Airflow, Kubeflow Pipelines, or Metaflow.
• Collaborate with AI/ML engineers to deploy machine learning models using , TensorFlow and Airflow orchestration.
• Containerize ML applications using Docker with Flask, FastAPI, or Django APIs.
• Support dataset versioning and experiment tracking using MLflow and DVC.
• Assist in maintaining model registries and ensuring reproducible ML workflows.
• Monitor deployed models for performance, data drift, and infrastructure health using tools such as Evidently AI, Prometheus, and Grafana.
• Support automated retraining workflows and model deployment processes.

Cloud & DevOps

• Assist in deploying and managing cloud infrastructure on AWS, GCP, or Azure.
• Support CI/CD pipeline development using GitHub Actions, GitLab CI, or Jenkins.
• Learn and contribute to Infrastructure as Code (IaC) using Terraform or CloudFormation.
• Work with Docker and Kubernetes for application deployment and orchestration.
• Monitor cloud resources and optimize infrastructure performance.
• Follow DevOps and DevSecOps best practices for secure deployments.

Required Skills

• Good understanding of Linux, shell scripting, and networking fundamentals.
• Basic knowledge of Python programming.
• Familiarity with Docker and Kubernetes.
• Understanding of Git and CI/CD concepts.
• Knowledge of cloud platforms such as AWS, Azure, or GCP.
• Basic understanding of machine learning workflows and model deployment.
• Familiarity with REST APIs using Flask, FastAPI, or Django.
• Strong analytical, debugging, and problem-solving skills.
• Good communication and willingness to learn new technologies.

Preferred Skills

• Exposure to MLflow, DVC, Airflow, Kubeflow, or Metaflow, apache kafka.
• Familiarity with Terraform or other Infrastructure as Code tools.
• Knowledge of monitoring tools such as Prometheus or Grafana.
• Understanding of model serving frameworks like BentoML, TorchServe, or TensorFlow Serving.
• Knowledge of DevSecOps tools like SonarQube is an advantage.

Eligibility

• Final-year B.Tech/B.E./M.Tech/MCA students or recent graduates in Computer Science, Information Technology, Artificial Intelligence, Machine Learning, or related fields.
• Strong interest in MLOps, Cloud Computing, DevOps, and AI infrastructure.
• Prior academic projects, internships, or open-source contributions in ML or cloud technologies are a plus.

What You'll Gain

• Hands-on experience with production-grade MLOps and cloud infrastructure.
• Opportunity to work on real-world AI/ML products and scalable deployments.
• Mentorship from experienced AI/ML and DevOps professionals.
• Exposure to modern MLOps tools, Kubernetes, cloud platforms, and CI/CD workflows.
• Potential Pre-Placement Offer (PPO) based on performance.

Who You'll Work With

- AI/ML Engineers, Backend Developers, Frontend Developers, QA Team

-Product Owners, Project Managers, and external Government or Enterprise Clients

What We’re Looking For:

• Strong experience in Python (3+ years).
• Hands-on experience with any database (SQL or NoSQL).
• Experience with frameworks like Flask, FastAPI, or Django.
• Knowledge of ORMs, API development, and unit testing.
• Familiarity with Git and Agile methodologies.

We are seeking a motivated and results-driven Tele Sales Executive to join our sales team. The ideal candidate will be responsible for generating leads, engaging potential clients, and driving sales of our technology solutions. This role requires excellent communication skills, a persuasive approach, and a strong focus on achieving sales targets. 

Key Responsibilities: 

- 1. Outbound Calls: Contact prospective and existing customers by phone to introduce, promote, and sell products & services. 

2. Lead Generation: Identify and qualify new sales leads from provided lists, referrals, and other sources. 

3. Sales Pitch: Deliver compelling sales pitches, respond to customer inquiries, and handle objections to close sales. 

4. Customer Engagement: Build and maintain positive relationships with customers, understanding their needs and offering appropriate solutions. 

5. Data Management: Accurately record and update customer information, interactions, and sales activity in the CRM system. 

6. Sales Targets: Meet or exceed individual and team sales goals and quotas. 

7. Feedback Collection: Gather and report customer feedback to help improve products, services, and sales strategies. 

Role & Responsibilities

1. Create innovative architectures based on business requirements.
2. Design and develop cloud-based solutions for global enterprises.
3. Coach and nurture engineering teams through feedback, design reviews, and best practice input.
4. Lead cross-team projects, ensuring resolution of technical blockers.
5. Collaborate with internal engineering teams, global technology firms, and the open-source community.
6. Lead initiatives to learn and apply modern and advanced technologies.
7. Oversee the launch of innovative products in high-volume production environments.
8. Develop and maintain high-quality software applications using JS frameworks (React, NPM, Node.js etc.,).
9. Utilize design patterns for backend technologies and ensure strong coding skills.
10. Deploy and manage applications on AWS cloud services, including ECS (Fargate), Lambda, and load balancers. Work with Docker to containerize services.
11. Implement and follow CI/CD practices using GitLab for automated build, test, and deployment processes.
12. Collaborate with cross-functional teams to design technical solutions, ensuring adherence to Microservice Design patterns and Architecture.
13. Apply expertise in Authentication & Authorization protocols (e.g., JWT, OAuth), including certificate handling, to ensure robust application security.
14. Utilize databases such as Postgres, MySQL, Mongo and DynamoDB for efficient data storage and retrieval.
15. Demonstrate familiarity with Big Data technologies, including but not limited to:

- Apache Kafka for distributed event streaming.

- Apache Spark for large-scale data processing.

- Containers for scalable and portable deployments.

Technical Skills:

1. 7+ years of hands-on development experience with JS frameworks, specifically MERN.
2. Strong coding skills in backend technologies using various design patterns.
3. Strong UI development skills using React.
4. Expert in containerization using Docker.
5. Knowledge of cloud platforms, specifically OCI, and familiarity with serverless technology, services like ECS, Lambda, and load balancers.
6. Proficiency in CI/CD practices using GitLab or Bamboo.
7. Strong knowledge of Microservice Design patterns and Architecture.
8. Expertise in Authentication and authorization protocols like JWT, and OAuth including certificate handling.
9. Experience working with high stream media data.
10. Experience working with databases such as Postgres, MySQL, and DynamoDB.
11. Familiarity with Big Data technologies related to Kafka, PySpark, Apache Spark, Containers, etc.
12. Experience with container Orchestration tools like Kubernetes.

• 3+ years’ experience developing and implementing enterprise-scale reports and dashboards.

• Proficiency with MS Power BI / SSRS.

• Knowledge of logical and physical data modeling concepts (relational and dimensional).

• Understanding of structured query language (SQL).

What you need to have: