Patdel Analytics is looking for AI / ML Engineer to join our dynamic team and embark on a rewarding career journey. Data Collection : Gather, preprocess, and clean data from various sources to create datasets suitable for training machine learning models. Feature Engineering : Select, extract, and engineer relevant features from data to improve model performance. Model Selection : Choose appropriate machine learning algorithms and models based on the problem at hand, such as regression, classification, clustering, or deep learning models. Model Training : Train machine learning models using historical data and employ techniques like supervised, unsupervised, and reinforcement learning. Hyperparameter Tuning : Optimize model performance by adjusting hyperparameters and fine - tuning the model to achieve the best results. Evaluation : Assess model performance using various metrics and techniques, such as cross - validation, ROC curves, and confusion matrices. Deployment : Deploy machine learning models into production systems, including web applications, mobile apps, or IoT devices. Continuous Improvement : Monitor model performance in real - world applications and retrain models as necessary to adapt to changing data patterns.

Patdel Analytics is looking for Project Manager to join our dynamic team and embark on a rewarding career journey. Coordinating with cross - discipline team members to make sure that all parties are on track with project requirements, deadlines, and schedules. Meeting with project team members to identify and resolve issues. Submitting project deliverables and ensuring that they adhere to quality standards. Preparing status reports by gathering, analyzing, and summarizing relevant information. Establishing effective project communication plans and ensuring their execution. Facilitating change requests to ensure that all parties are informed of the impacts on schedule and budget. Coordinating the development of user manuals, training materials, and other documents as needed to enable successful implementation and turnover of the process or system to the clients. Identifying and developing new opportunities with clients. Obtaining customer acceptance of project deliverables. Managing customer satisfaction within the project transition period. Conducting post - project evaluation and identifying successful and unsuccessful project elements.

We are seeking a skilled and experienced DevOps Engineer with expertise in architecting, implementing, and managing hybrid cloud infrastructure to enable seamless deployment and scaling of high-performance applications and machine learning workloads. Proven experience in cloud services, on-premises systems, container orchestration, automation, and multi-database management. Key Responsibilities & Experience : - Designed, implemented, and managed scalable AWS infrastructure leveraging services such as EC2, ECS, Lambda, S3, DynamoDB, Cognito, SageMaker, Amazon ECR, SES, Route 53, VPC Peering, and Site-to-Site VPN to support secure, high-performance, and resilient cloud environments. - Applied best practices in network security, including firewall configuration, IAM policy management. - Architected and maintained large-scale, multi-database systems integrating PostgreSQL, MongoDB, DynamoDB, and Elasticsearch to support millions of records, low-latency search, and real-time analytics. - Built and maintained CI/CD pipelines using GitHub Actions and Jenkins, enabling automated testing, Docker builds, and seamless deployments to production. - Managed containerized deployments using Docker, and orchestrated services using Amazon ECS for scalable and resilient application environments. - Implemented and maintained IaC frameworks using Terraform, AWS CloudFormation, and Ansible to ensure consistent, repeatable, and scalable infrastructure deployments. - Developed Ansible playbooks to automate system provisioning, OS-level configurations, and application deployments across hybrid environments. - Configured Amazon CloudWatch and Zabbix for proactive monitoring, health checks, and custom alerts to maintain system reliability and uptime. - Administered Linux-based servers, applied system hardening techniques, and maintained OS-level and network security best practices. - Managed SSL/TLS certificates, configured DNS records, and integrated email services using Amazon SES and SMTP tools. - Deployed and managed infrastructure for ML workloads using AWS SageMaker, optimizing model training, hosting, and resource utilization for cost-effective performance. Preferred Qualifications : - 3+ years of experience in DevOps, Cloud Infrastructure - Bachelors degree in Computer Science, Engineering - Experience deploying and managing machine learning models - Hands-on experience managing multi-node Elasticsearch clusters and designing scalable, high-performance search infrastructure. - Experience designing and operating hybrid cloud architectures, integrating on-premises and cloud-based systems Job Types: Full-time, Permanent Pay: ₹300,000.00 - ₹1,200,000.00 per year Benefits: Flexible schedule Paid sick time Paid time off Ability to commute/relocate: Mohali, Punjab: Reliably commute or planning to relocate before starting work (Preferred) Education: Bachelor's (Preferred) Experience: DevOps: 3 years (Required) Work Location: In person Speak with the employer +91 8360518086

Job Title: AI/ML Engineer Job Summary We are seeking a talented and passionate AI/ML Engineer with at least 3 years of experience to join our growing data science and machine learning team. The ideal candidate will have hands-on experience in building and deploying machine learning models, data preprocessing, and working with real-world datasets. You will collaborate with cross-functional teams to develop intelligent systems that drive business value. Key Responsibilities ● Design, develop, and deploy machine learning models for various business use cases. ● Analyze large and complex datasets to extract meaningful insights. ● Implement data preprocessing, feature engineering, and model evaluation pipelines. ● Work with product and engineering teams to integrate ML models into production environments. ● Conduct research to stay up to date with the latest ML and AI trends and technologies. ● Monitor and improve model performance over time. Required Qualifications ● Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. ● Minimum 3 years of hands-on experience in building and deploying machine learning models. ● Strong proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, and XGBoost. ● Experience with training, fine-tuning, and evaluating ML models in real-world applications. ● Proficiency in Large Language Models (LLMs) – including experience using or fine-tuning models like BERT, GPT, LLaMA, or open-source transformers. ● Experience with model deployment, serving ML models via REST APIs or microservices using frameworks like FastAPI, Flask, or TorchServe. ● Familiarity with model lifecycle management tools such as MLflow, Weights & Biases, or Kubeflow. ● Understanding of cloud-based ML infrastructure (AWS SageMaker, Google Vertex AI, Azure ML, etc.). ● Ability to work with large-scale datasets, perform feature engineering, and optimize model performance. ● Strong communication skills and the ability to work collaboratively in cross-functional teams. Job Types: Full-time, Permanent Pay: ₹300,000.00 - ₹1,500,000.00 per year Benefits: Flexible schedule Paid sick time Paid time off Ability to commute/relocate: Mohali, Punjab: Reliably commute or planning to relocate before starting work (Preferred) Experience: Ai/ML: 2 years (Preferred) Work Location: In person