Data Analyst Associate - Data Management

Job Title: Associate AI/ML Engineer

Location: Gurugram, Haryana

Employment Type: Full-Time

About Aaizel Tech

Aaizel Tech is a pioneering tech startup at the intersection of cybersecurity, AI, geospatial solutions, and more. We drive innovation by delivering transformative technology solutions across industries. As a growing startup, we are looking for passionate and versatile professionals eager to work on cutting-edge projects in a dynamic environment.

Role Overview

As a Associate AI/ML Engineer at Aaizel Tech, you will lead the design, development, and deployment of advanced Machine Learning models and AI solutions. You will work on projects ranging from predictive analytics and NLP to computer vision and anomaly detection. You will also mentor a team of AI/ML professionals, collaborate with cross-functional teams, and drive innovation by integrating state-of-the-art research with scalable production systems.

Key Responsibilities

1. Model Development & Optimization

Design & Implementation:

• Architect and develop end-to-end ML solutions for applications such as predictive analytics, anomaly detection, computer vision, and NLP.
• Utilize advanced techniques including deep learning (CNNs, RNNs), reinforcement learning, and generative models (GANs) to address complex challenges.

Optimization:

• Fine-tune model parameters using techniques such as hyperparameter tuning (Grid Search, Bayesian Optimization, Neural Architecture Search).
• Optimize models for both accuracy and inference speed to meet real-time processing requirements.

2. Advanced Data Engineering & Integration

Data Pipeline Development:

• Build robust ETL pipelines using libraries like Pandas, NumPy, and PySpark to process large-scale datasets from satellite imagery, IoT sensors, and real-time streams.
• Integrate data from diverse sources (APIs, databases, big data platforms like Hadoop and Apache Kafka) to support real-time analytics.

Data Quality & Preprocessing:

• Implement data cleansing, feature engineering, and transformation pipelines to ensure high-quality inputs for ML models.

3. Research & Innovation

Algorithm Research:

• Conduct research on state-of-the-art ML techniques including Transfer Learning, Transformer models, and AutoML to enhance model performance.
• Innovate new algorithms for specialized tasks such as geospatial analysis, environmental modeling, or cybersecurity threat detection.

Prototyping & Experimentation:

• Develop proof-of-concept models and prototypes to validate new approaches before production deployment.

4. Deployment, MLOps & Performance Monitoring

Model Deployment:

• Deploy models using containerization (Docker) and orchestration tools (Kubernetes) to ensure scalable and efficient production environments.
• Work with cloud platforms (AWS, Azure, GCP) and model serving solutions (TensorFlow Serving, ONNX, TorchServe) for high-throughput inference.

MLOps & Lifecycle Management:

• Implement CI/CD pipelines for ML models, ensuring seamless updates and versioning.
• Develop monitoring dashboards (using Prometheus, Grafana) to track model performance and trigger retraining based on real-time feedback.

5. Collaboration & Leadership

Cross-Functional Teamwork:

• Collaborate closely with data engineers, software developers, domain experts, and product managers to integrate AI solutions into end-to-end products.

Mentorship & Code Quality:

• Provide technical leadership and mentorship to junior AI/ML engineers, ensuring adherence to coding standards and best practices.
• Participate in code reviews, maintain detailed documentation, and foster a culture of continuous learning.

Recommended Technology Stack

Backend Framework:

• Python (Django/FastAPI): Ideal for API integration, leveraging Python’s rich AI/ML ecosystem.

AI/ML Frameworks:

• PyTorch + Hugging Face Transformers + scikit-learn: For flexibility in research, multilingual NLP tasks, and classical ML pipelines.

Data Engineering:

• Apache Kafka + Apache Spark + Apache NiFi: To handle both real-time data streaming and batch processing.

Database & Storage:

• PostgreSQL with TimescaleDB extension: For structured and time-series data storage.

DevOps & Monitoring:

• Docker, Kubernetes, GitLab CI/CD, Prometheus/Grafana: For containerized deployments, continuous integration, and comprehensive monitoring.

Media Processing:

• OpenCV, FFmpeg, Tesseract OCR, Wav2Vec2: To support image, video, and speech-to-text processing where needed.

Required Skills & Qualifications

Technical Expertise:

• Experience:
• 5+ years in Machine Learning, AI research, or a related field with a proven track record of delivering production-level AI solutions.
• Programming & Frameworks:
• Expertise in Python and hands-on experience with frameworks like PyTorch, TensorFlow, and scikit-learn.
• Experience with Hugging Face Transformers for NLP applications.
• Data Engineering:
• Proficiency in building data pipelines using Pandas, NumPy, PySpark, and integrating data from diverse sources.
• Familiarity with big data platforms and real-time data processing frameworks.
• Model Deployment & MLOps:
• Hands-on experience with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for ML models.
• Experience with cloud deployment and model serving solutions.
• Research & Innovation:
• Demonstrated ability to apply advanced ML techniques (deep learning, transfer learning, reinforcement learning) to solve real-world problems.
• Testing & Optimization:
• Strong background in model evaluation, hyperparameter tuning, and performance optimization.

Soft Skills:

• Exceptional problem-solving and analytical abilities.
• Strong communication skills, with the ability to present complex technical concepts to diverse stakeholders.
• Leadership and mentoring experience, with a collaborative approach to working in cross-functional teams.
• Ability to thrive in a fast-paced, dynamic environment and drive continuous innovation.

Educational Background:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field from a reputed institution.

What We Offer

• Innovative Projects: Engage in cutting-edge AI/ML projects that influence product strategy and technological innovation.
• Professional Growth: Opportunities for continuous learning, mentorship, and career advancement.
• Collaborative Culture: Work within a diverse team of experts passionate about pushing the boundaries of technology.
• Impactful Work: Play a key role in shaping AI-driven solutions and driving real-world impact.

Who Are We

A research-oriented company with expertise in computer vision and artificial intelligence, at its core, Orbo is a comprehensive platform of AI-based visual enhancement stack. This way, companies can find a suitable product as per their need where deep learning powered technology can automatically improve their Imagery.

ORBO's solutions are helping BFSI, beauty and personal care digital transformation and Ecommerce image retouching industries in multiple ways.

WHY US

• Join top AI company
• Grow with your best companions
• Continuous pursuit of excellence, equality, respect
• Competitive compensation and benefits

You'll be a part of the core team and will be working directly with the founders in building and iterating upon the core products that make cameras intelligent and images more informative.

To learn more about how we work, please check out

https://www.orbo.ai/.

Description:

We are looking for a computer vision engineer to lead our team in developing a factory floor analytics SaaS product. This would be a fast-paced role and the person will get an opportunity to develop an industrial grade solution from concept to deployment.

Responsibilities:

• Research and develop computer vision solutions for industries (BFSI, Beauty and personal care, E-commerce, Defence etc.)
• Lead a team of ML engineers in developing an industrial AI product from scratch
• Setup end-end Deep Learning pipeline for data ingestion, preparation, model training, validation and deployment
• Tune the models to achieve high accuracy rates and minimum latency
• Deploying developed computer vision models on edge devices after optimization to meet customer requirements

Requirements:

• Bachelor’s degree
• Understanding about depth and breadth of computer vision and deep learning algorithms.
• Experience in taking an AI product from scratch to commercial deployment.
• Experience in Image enhancement, object detection, image segmentation, image classification algorithms
• Experience in deployment with OpenVINO, ONNXruntime and TensorRT
• Experience in deploying computer vision solutions on edge devices such as Intel Movidius and Nvidia Jetson
• Experience with any machine/deep learning frameworks like Tensorflow, and PyTorch.
• Proficient understanding of code versioning tools, such as Git

Our perfect candidate is someone that:

• is proactive and an independent problem solver
• is a constant learner. We are a fast growing start-up. We want you to grow with us!
• is a team player and good communicator

What We Offer:

• You will have fun working with a fast-paced team on a product that can impact the business model of E-commerce and BFSI industries. As the team is small, you will easily be able to see a direct impact of what you build on our customers (Trust us - it is extremely fulfilling!)
• You will be in charge of what you build and be an integral part of the product development process
• Technical and financial growth!

Responsibilities:

- Design, implement, and maintain cloud infrastructure solutions on Microsoft Azure, with a focus on scalability, security, and cost optimization.

- Collaborate with development teams to streamline the deployment process, ensuring smooth and efficient delivery of software applications.

- Develop and maintain CI/CD pipelines using tools like Azure DevOps, Jenkins, or GitLab CI to automate build, test, and deployment processes.

- Utilize infrastructure-as-code (IaC) principles to create and manage infrastructure deployments using Terraform, ARM templates, or similar tools.

- Manage and monitor containerized applications using Azure Kubernetes Service (AKS) or other container orchestration platforms.

- Implement and maintain monitoring, logging, and alerting solutions for cloud-based infrastructure and applications.

- Troubleshoot and resolve infrastructure and deployment issues, working closely with development and operations teams.

- Ensure high availability, performance, and security of cloud infrastructure and applications.

- Stay up-to-date with the latest industry trends and best practices in cloud infrastructure, DevOps, and automation.

Requirements:

- Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent work experience).

- Minimum of four years of proven experience working as a DevOps Engineer or similar role, with a focus on cloud infrastructure and deployment automation.

- Strong expertise in Microsoft Azure services, including but not limited to Azure Virtual Machines, Azure App Service, Azure Storage, Azure Networking, Azure Security, and Azure Monitor.

- Proficiency in infrastructure-as-code (IaC) tools such as Terraform or ARM templates.

- Hands-on experience with containerization and orchestration platforms, preferably Azure Kubernetes Service (AKS) or Docker Swarm.

- Solid understanding of CI/CD principles and experience with relevant tools such as Azure DevOps, Jenkins, or GitLab CI.

- Experience with scripting languages like PowerShell, Bash, or Python for automation tasks.

- Strong problem-solving and troubleshooting skills with a proactive and analytical mindset.

- Excellent communication and collaboration skills, with the ability to work effectively in a team environment.

- Azure certifications (e.g., Azure Administrator, Azure DevOps Engineer, Azure Solutions Architect) are a plus.

1. Work across the entire landscape that spans network, compute, storage, databases, applications, and business domain
2. Use the Big Data and AI-driven features of vuSmartMaps to provide solutions that will enable customers to improve the end-user experience for their applications
3. Create detailed designs, solutions and validate with internal engineering and customer teams, and establish a good network of relationships with customers and experts
4. Understand the application architecture and transaction-level workflow to identify touchpoints and metrics to be monitored and analyzed
5. Analytics and analysis of data and provide insights and recommendations
6. Constantly stay ahead in communicating with customers. Manage planning and execution of platform implementation at customer sites.
7. Work with the product team in developing new features, identifying solution gaps, etc.​
8. Interest and aptitude in learning new technologies - Big Data, no SQL databases, Elastic Search, Mongo DB, DevOps.​

1. At least 2+ years of experience in IT Infrastructure Management
2. Experience in working with large-scale IT infra, including applications, databases, and networks.​
3. Experience in working with monitoring tools, automation tools
4. Hands-on experience in Linux and scripting.
5. Knowledge/Experience in the following technologies will be an added plus:​ ​ElasticSearch, Kafka, Docker Containers, MongoDB, Big Data, SQL databases, ELK stack, REST APIs, web services, and JMX.

Who we are

At Criteo, our culture is as unique as it is diverse. From our offices around the world or from home, our incredible team of 2,700 Criteos collaborates to develop an open and inclusive environment. We aim to create a place where people can grow and learn from each other while having a meaningful impact. We work together to achieve our goals, push boundaries, and share successes. All of this supports us in our mission to power the world’s marketers with trusted and impactful advertising.

At Criteo, we believe the future is wide open when it includes everyone. We are committed to creating an environment where all Criteos feel a sense of belonging. We nourish our diversity by listening to all cultures within Criteo - and there are many. We are proud to be a global team and conscious that it takes people with different perspectives, thoughts and cultures to succeed. We want you to come as you are so we can succeed together.