AI Machine Learning Engineer
AI Machine Learning Engineer
Posted on :
18-04-2025
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1 Vacancy
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Jobs by Experience
5years
Monthly Salary
Not Disclosed
Salary Not Disclosed
Vacancy
1 Vacancy
Posted on :
18-04-2025
Job Description
- Develop & optimize AI/ML models for NLP Computer Vision Predictive Analytics and Recommendation Systems.
- Implement cuttingedge AI solutions including RAG LLM finetuning multimodal AI and prompt engineering.
- Integrate AI models from OpenAI Claude Gemini and opensource alternatives into our EdTech platform.
- Design train and deploy models using TensorFlow PyTorch Scikitlearn LangChain and Hugging Face Transformers.
- Process largescale datasets using Big Data technologies (Spark Databricks Hadoop).
- Develop and maintain scalable data pipelines for realtime and batch processing.
- Deploy ML models in production using cloudbased AI services (AWS SageMaker Google Vertex AI Azure ML).
- Implement MLOps best practices for model monitoring retraining versioning and deployment automation.
- Optimize inference performance for edge and cloud AI applications.
- Collaborate with crossfunctional teams to integrate AI features into products and improve user experience.
- Document model architectures training processes and evaluation metrics.
- Stay updated with the latest advancements in AI ML and deep learning research.
Requirements
- Education: Master s degree in AI ML Data Science or related fields (mandatory).
- Experience: 5 years in AI/ML development data science or AI engineering.
- Programming: Proficiency in Python (NumPy Pandas Scikitlearn PyTorch TensorFlow); familiarity with R or Java is a plus.
- AI & ML Frameworks: Handson experience with TensorFlow PyTorch Keras LangChain Hugging Face Transformers.
- Cloud & Big Data: Experience with AWS GCP or Azure AI services Big Data technologies like Spark Kafka and Databricks.
- MLOps & Deployment: Strong knowledge of CI/CD pipelines for ML model monitoring and retraining strategies.
- Mathematical & Statistical Skills: Solid understanding of probability statistics optimization techniques and deep learning architectures.
Benefits
- Monday to Friday with flexible working hours
- Work on cuttingedge AI & ML solutions in the EdTech domain.
- Provident fund and health insurance for employees
- Collaborate with global AI vendors and leverage the latest advancements in LLMs RAG and Generative AI.
- Dynamic and collaborative work environment.
- Competitive salary and growth opportunities.
Architecting AI-Powered Systems: Design, develop, and optimize AI-driven applications, integrating LLMs, Retrieval-Augmented Generation (RAG), NLP, and Generative AI. Implement AI/ML pipelines, working with OpenAI, Anthropic (Claude), Google Gemini, Mistral, and Meta AI. Architect scalable microservices with AI-powered automation, chatbots, and recommendation systems. Cloud & DevOps Leadership: Oversee AWS-based cloud architecture, including EC2, EKS (Kubernetes), Lambda, RDS, IAM, and security best practices. Implement Infrastructure as Code (IaC) using Terraform, AWS CloudFormation for scalable deployments. Ensure high availability, fault tolerance, and auto-scaling of cloud services. Lead containerization strategies with Docker and Kubernetes (K8s), optimizing workloads in AWS EKS. Full-Stack System Design & API Development: Architect and oversee development across , , Flutter, Flutter Web, and Python-based APIs. Ensure secure and efficient API development in Python (FastAPI, Flask), , Laravel. Optimize database performance using Vitess (MySQL Sharding), PostgreSQL, Redis, and Snowflake. Monitoring, Security, and Performance Optimization: Set up Grafana, Prometheus, and OpenTelemetry for observability and real-time system monitoring. Implement security best practices, ensuring compliance with SOC 2, ISO 27001, GDPR. Manage zero-downtime deployments using Blue-Green Deployment, Canary Releases, and Feature Flags. Drive performance optimizations across frontend, backend, and AI workloads. Cross-Team Collaboration & Leadership: Work closely with AI engineers, DevOps specialists, full-stack developers, and product teams to design scalable systems. Lead Agile methodologies, including Scrum, Sprint Planning, and Code Reviews. Mentor engineers and establish architectural best practices for long-term product scalability. Requirements: Technical Skills & Experience: 10+ years of experience in full-stack development, cloud architecture, and AI-driven applications. Expertise in AI & ML systems: RAG, LLM fine-tuning, LangChain, Hugging Face, OpenAI APIs. Cloud & DevOps: Deep expertise in AWS services, Terraform, Kubernetes (EKS), Docker, CI/CD pipelines. Full-Stack Development: Experience in , , Flutter, Flutter Web, and Python (FastAPI, Flask, Django). Database Expertise: MySQL (Vitess), PostgreSQL, Redis, Snowflake, and data warehousing solutions. Monitoring & Security: Strong knowledge of Grafana, Prometheus, OpenTelemetry, IAM policies, and cloud security.
Employment Type
Full Time
Key Skills
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