Engro Technologies
Website:
engro.io
Job details:
Senior AI/ML EngineerAbout Engro Technologies
Engro Technologies is a dynamic media tech company at the forefront of digital transformation. We specialize in leveraging innovative solutions like cloud computing, IoT, AI, and data science to empower businesses, enhance efficiency, and streamline processes. Committed to excellence and customer satisfaction, we deliver high-quality IT services from our offshore centre in India and onshore locations, helping clients excel in a competitive digital landscape. Our culture fosters creativity, collaboration, and continuous learning, driving our team to achieve outstanding results in every project.
Website: https://engro.io/
https://engro.ai/
About the Role
We are seeking a highly skilled and motivated Senior AI/ML Engineer to design, develop, and deploy scalable artificial intelligence and machine learning solutions. The ideal candidate will have strong technical expertise in machine learning, data engineering, and MLOps, with hands-on experience building production-ready AI applications. You will work closely with cross-functional teams to develop intelligent solutions that address complex business challenges and drive innovation.
Project Responsibilities
As part of the IRIMS platform, you will be responsible for developing the intelligence layer of the solution. This includes building algorithms that establish 4-week behavioural baselines, developing correlation logic to identify relationships between network drops and POS failures, and implementing MLOps pipelines that automatically retrain machine learning models before peak retail seasons.
Key Skills
· Machine Learning
· AIOps
· Data Engineering
· Python
· Scikit-learn
· TensorFlow
· Time-series Forecasting (ARIMA, Prophet, or Deep Learning equivalents)
· Kubernetes Model Deployment
· Kafka Data Streaming
Key Responsibilities
· Design, develop, test, and deploy scalable AI/ML solutions from concept to production.
· Build and optimize machine learning models, pipelines, and frameworks for enterprise applications.
· Develop algorithms for behavioural baseline analysis, anomaly detection, and predictive analytics.
· Implement correlation logic to identify relationships between operational events and business outcomes.
· Build and maintain MLOps pipelines for automated model training, deployment, monitoring, and retraining.
· Collaborate with engineering, product, data science, and business teams to deliver AI-driven solutions.
· Develop data processing pipelines and perform feature engineering to improve model performance.
· Deploy and manage machine learning workloads on Kubernetes-based environments.
· Implement real-time data processing and streaming solutions using Kafka.
· Monitor model performance, troubleshoot production issues, and continuously optimize AI solutions.
· Stay current with emerging AI/ML technologies, frameworks, and industry best practices.
· Ensure AI solutions follow responsible AI, security, and governance standards.
· Mentor junior engineers and contribute to technical knowledge sharing within the team.
Qualifications
· Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.
· 4–6 years of hands-on experience in AI/ML development and deployment.
· Strong programming skills in Python with expertise in TensorFlow, PyTorch, and Scikit-learn.
· Experience building and deploying production-grade machine learning models.
· Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
· Experience with MLOps tools such as Kubeflow, MLflow, Airflow, or similar platforms.
· Strong understanding of data engineering, feature engineering, model optimization, and model evaluation.
· Experience with deep learning, NLP, computer vision, recommendation systems, or predictive analytics.
· Experience deploying AI solutions using Docker and Kubernetes.
· Familiarity with distributed data processing and Kafka-based streaming architectures.
· Strong analytical, problem-solving, and debugging skills.
· Excellent communication and collaboration skills.
Preferred Skills
· Hands-on experience with Large Language Models (LLMs) and Generative AI.
· Experience with AI-powered SaaS or enterprise applications.
· Familiarity with containerization and orchestration using Docker and Kubernetes.
· Experience implementing scalable MLOps pipelines and CI/CD for machine learning.
· Knowledge of cloud-native AI services and distributed computing frameworks.
· Exposure to AIOps platforms and observability solutions.
Click on Apply to know more.
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