Machine Learning Engineer

Job Role : Azure DevSecOps Engineer (Security-Focused)

Experience : 12 to 18 Years

Location : Preferably Delhi NCR (Hybrid); Remote possible with 1–2 office visits per quarter (Gurgaon)

Joining Timeline : Max 45 days (Buyout option available)

Work Mode : Full-time | 5 Days Working

About the Role :

We are looking for a highly experienced Azure DevSecOps Engineer with a strong focus on cloud security practices.

This role is 60–70% security-driven, involving threat modeling, secure cloud architecture, and infrastructure security on Azure using Terraform.

Key Responsibilities :

• Architect and maintain secure, scalable Azure cloud infrastructure using Terraform.
• Implement security best practices : IAM, threat modeling, network security, data protection, and compliance (e.g., GDPR).
• Build CI/CD pipelines and automate deployments using Azure DevOps, Jenkins, Prometheus.
• Monitor, analyze, and proactively improve security posture.
• Collaborate with global teams to ensure secure design, development, and operations.
• Stay updated on cloud security trends and lead mitigation efforts.

Mandatory Skills :

Azure, Terraform, DevSecOps, Cloud Security, Threat Modelling, IAM, CI/CD (Azure DevOps), Docker, Kubernetes, Prometheus, Infrastructure as Code (IaC), Compliance Frameworks (GDPR)

Preferred Certifications :

Certified DevSecOps Professional (CDP), Microsoft Azure Certifications

Job Description:

We are seeking a Cloud & AI Platform Engineer to design and operate AI-native infrastructure that supports large-scale machine learning, generative AI, and agentic AI systems. 

This role will focus on building secure, scalable, and automated multi-cloud platforms across AWS, Azure, GCP, and hybrid on-prem environments, enabling teams to deploy LLMs, AI agents, and data-driven applications reliably in production. 

You will work at the intersection of cloud engineering, MLOps, LLMOps, DevOps, and data infrastructure, helping build platforms that support RAG pipelines, vector search, AI model lifecycle management, and AI observability. 

Key Responsibilities

AI & Agentic Infrastructure 

• Design infrastructure to support agentic AI systems, autonomous agents, and multi-agent workflows. 
• Build scalable runtime environments for LLM orchestration frameworks. 
• Enable deployment of AI copilots, assistants, and autonomous decision systems. 

Common frameworks may include: 

• LangChain 
• LlamaIndex 
• AutoGPT 

LLMOps & AI Model Lifecycle 

Design and manage LLMOps pipelines for the full lifecycle of large language models: 

• Model deployment 
• Prompt management 
• Versioning 
• Evaluation and testing 
• Model monitoring 

Integrate with AI platforms such as: 

• Azure Machine Learning 
• Amazon SageMaker 
• Vertex AI 

Retrieval-Augmented Generation (RAG) Infrastructure 

Design and optimize RAG pipelines that integrate enterprise knowledge with LLMs. 

Responsibilities include: 

• Document ingestion pipelines 
• Embedding generation workflows 
• Knowledge indexing 
• Query orchestration 
• Retrieval optimization 
• Support scalable semantic search architectures. 

Vector Database & Knowledge Infrastructure 

Deploy and manage vector databases used for AI applications and semantic retrieval. 

Common technologies include: 

• Pinecone 
• Weaviate 
• Milvus 
• FAISS 

Responsibilities include: 

• Index optimization 
• Query latency tuning 
• Scalable embedding storage 
• Hybrid search architecture 

Multi-Cloud AI Infrastructure 

Design and maintain AI-ready infrastructure across: 

• Amazon Web Services 
• Microsoft Azure 
• Google Cloud Platform 

Key responsibilities include: 

• GPU infrastructure management 
• Distributed training environments 
• Hybrid cloud integrations with on-prem data centers 
• Infrastructure scaling for AI workloads 

Data Platforms & Integration 

• Support deployment and optimization of data lakes, data warehouses, and streaming platforms. 
• Work with data engineering teams to ensure secure and scalable data infrastructure. 

Cloud Architecture & Infrastructure 

• Design and implement scalable multi-cloud infrastructure across Azure, AWS, and Google Cloud. 
• Build hybrid cloud architectures integrating on-premise environments with cloud platforms. 
• Implement high availability, disaster recovery, and auto-scaling architectures for AI workloads. 

DevOps, Platform Engineering & Automation 

Build automated cloud infrastructure using modern DevOps practices. 

Tools may include: 

• Terraform 
• Docker 
• Kubernetes 
• GitHub Actions 

Responsibilities include: 

• Infrastructure as Code (IaC) 
• Automated deployments 
• CI/CD pipelines for AI models and services 
• Platform reliability and scalability 

AI Observability & Monitoring 

Implement observability frameworks to monitor AI systems in production. 

This includes: 

• Model performance monitoring 
• Prompt evaluation 
• Hallucination detection 
• Latency and throughput analysis 
• Cost monitoring for LLM usage 

Tools may include: 

• Arize AI 
• WhyLabs 
• Weights & Biases 

Security, Governance & Responsible AI 

Ensure AI systems follow strong governance and security practices. 

Responsibilities include: 

• Data privacy and compliance 
• Model governance frameworks 
• Secure model deployment 
• Monitoring model bias and drift 
• AI risk management 

Support enterprise frameworks for Responsible AI and AI compliance. 

Data & Security 

• Experience with data lake architectures, distributed storage, and ETL pipelines 
• Knowledge of data security, encryption, IAM, and compliance frameworks 
• Familiarity with AI governance and responsible AI practices 

Required Skills 

Cloud & Infrastructure 

• Strong experience in Azure (must have), AWS or GCP 
• Hybrid and multi-cloud architecture 
• GPU infrastructure management 

DevOps & Automation 

• Kubernetes 
• Docker 
• Terraform 
• CI/CD pipelines 

AI / ML Platforms 

• MLOps pipelines 
• Model deployment 
• Model monitoring 

AI Application Infrastructure 

• Vector databases 
• RAG pipelines 
• LLM orchestration frameworks 

Programming 

Experience in one or more languages: 

• Python 
• Go 
• Java 
• TypeScript 

Preferred Qualifications 

• Experience building AI copilots or autonomous agents 
• Knowledge of distributed model training - Knowledge of GPU infrastructure and distributed training 
• Familiarity with AI evaluation frameworks - Familiarity with model monitoring, drift detection, and AI observability 
• Experience building enterprise AI platforms 

Education & Experience 

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field 
• 4–8+ years experience in cloud infrastructure, DevOps, or platform engineering 
• Experience working in data-driven or AI-focused environments 

What Success Looks Like 

• Reliable ML model deployment pipelines - Reliable infrastructure for LLMs and AI agents, Scalable RAG knowledge platforms 
• Efficient multi-cloud infrastructure management - Fast deployment cycles for AI products 
• Secure and scalable AI-ready cloud platforms 
• Strong automation and governance across cloud and AI systems 

NEED TO HAVE :

1) Have some knowledge of front end like React.JS

2) HTML, CSS

3) Strong in Javascript concepts

4) Good communication skills

5) Loves to code

GOOD TO HAVE :

1) Experience with type script will be a plus

2) Experience with Nest.JS framework will be a plus

3) Strong hold on ES6 principles.

4) Familiar with TDD ( Test Driven Development ) will be a plus.

5) Familiar with working in CI / CD will be a plus

6) Micro-Service architecture knowledge will be an added benefit.

WhatsApp us on nine three one six one two zero one three two

Position Summary

We are seeking an experienced Senior Test Engineer to ensure the quality and reliability of our full-stack mobile and web applications built with React Native and Ruby on Rails. In this role, you will work closely with cross-functional teams to design and execute testing strategies, develop automation frameworks using Selenium and BrowserStack, and contribute to the continuous improvement of our QA processes.

Key Responsibilities

1. Testing Strategy and Execution:

• Develop and execute comprehensive test plans for mobile and web applications.

• Conduct functional, regression, performance, compatibility, and security testing.

• Collaborate with developers, product managers, and stakeholders to clarify requirements and ensure test coverage.

2. Automation Frameworks and Tools:

• Build and maintain test automation frameworks for web and mobile applications using Selenium and BrowserStack.

• Create and maintain automated test scripts for cross-browser and cross-device testing.

• Integrate automated tests into CI/CD pipelines using tools like Jenkins, GitHub Actions.

3. Mobile and Web Application Testing:

• Perform testing of React Native mobile applications across various devices and platforms using BrowserStack.

• Validate web application functionality across multiple browsers and screen resolutions with Selenium.

• Ensure the performance and responsiveness of applications on both mobile and web platforms.

4. Defect Management and Reporting:

• Log and track defects in tools like JIRA , working closely with developers for resolution.

• Provide detailed test reports and feedback to stakeholders, highlighting risks and improvement opportunities.

5. Performance and Load Testing:

• Execute backend performance and load testing for Ruby on Rails applications using tools like JMeter.

• Analyze application performance metrics to identify potential bottlenecks.

6. Process Improvement:

• Actively contribute to improving QA processes and adopting best practices for testing and automation.

• Participate in Agile/Scrum ceremonies, ensuring quality is integrated into each sprint cycle.

• Help with internal and external audits inline with Quality Management System.

7. Documentation and Knowledge Sharing:

• Maintain detailed documentation of test cases, automation scripts, and testing processes.

• Share insights and technical knowledge with team members to support their growth.

Qualifications and Skills

1. Technical Expertise:

• Hands-on experience in testing mobile applications built with React Native.

• Experience in backend testing for Ruby on Rails, including API testing using tools like Postman or Swagger.

• Proficiency with automation frameworks such as Selenium and tools like BrowserStack.

2. Automation Skills:

• Strong skills in developing and executing automated test cases for web and mobile applications.

• Knowledge of programming languages like Java, JavaScript, or Python for automation scripting.

• Experience integrating test automation into CI/CD workflows.

3. Problem-Solving and Collaboration:

• Ability to analyze complex systems, troubleshoot issues, and propose solutions.

• Strong collaboration skills with the ability to work closely with cross-functional teams.

4. Industry Knowledge:

• Familiarity with Agile methodologies and test-driven development practices.

• Understanding of best practices in security, performance, and accessibility testing.

• Exposure to Health Tech and related domains is a plus.

• Exposure to start up environment is a plus.

5. Preferred Skills:

• Experience with cloud environments (e.g., AWS, Azure, GCP) for testing and deployment.

• Knowledge of SQL/NoSQL databases for database validation and testing.

• Awareness of mobile app deployment processes for App Store and Google Play.

Education and Experience

• Bachelor’s degree in Computer Science, Software Engineering, or a related field.

• 4+ years of QA/testing experience with expertise in mobile and web application testing.

• Hands-on experience with React Native and Ruby on Rails applications is highly preferred.

Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible working hours and remote work opportunities.

• Professional development and training reimbursement.

We are hiring Unity Developers, who will be responsible for planning and implementing game functionality, building the game code, identifying bottlenecks, and ensuring the quality of the finished product. You may also be required to build patches and install game updates.

To ensure success as a Unity Developer, you should have extensive experience working with Unity and Unity3D software, excellent coding skills, and a good eye for detail. A top-class Unity Developer can visualize, design, and code games that speak directly to the target audience.

Unity Developer Responsibilities:

• Meeting with the design team to discuss gaming ideas and specifications.
• Establishing strategy and development pipelines.
• Planning and implementing game functionality.
• Transforming design ideas into functional games.
• Designing and building game codes.
• Identifying and fixing code errors and game bottlenecks.
• Testing game functionality and theme dynamics.
• Ensuring products conform to high industry standards.
• Designing and building game patches and upgrades.

Unity Developer Requirements:

• Bachelor’s degree in Computer Science, Computer Engineering or a similar field.
• Previous experience working as a Unity or Unity3D Developer.
• In-depth knowledge of Unity and Unity3D software.
• Knowledge of 3D development and integrated game physics.
• Experience with console and mobile game development.
• Good communication skills.
• Experience with memory and space optimization.
• Knowledge of scripting, animation, session management, and textures.
• Good troubleshooting skills.
• Excellent attention to detail.

1. Experienced iOS Developer with full-time work experience in developing iOS apps for iPhone, iPad, iPod.
2. Should be proficient in Swift and Objective C and use Xcode, Cocoa libraries, and other third-party libraries to develop apps.

• Delivering a comprehensive service to enquiring customers
• Possibly delegating certain customer enquiries to specific teams
• Managing a large number of incoming calls and emails
• Managing customers’ accounts
• Keeping a record of customer interaction and details of actions taken
• Communicating with internal teams to discuss sales targets
• Generating sales leads, building sustainable relationships where necessary
• Reporting back on results