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AI/ML Engineer

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Onsite

AI/ML Engineer

Moreyeahs

AI/ML Engineer

Skills

Google Cloud PlatformSQL QueriesMongoDBData EngineeringDeep LearningDockerFlaskPythonMicroservicesPyTorchTensorFlowPostgreSQLMySQLAWS LambdaRedisGitLabJenkinsMachine LearningAIAWSGitHubKubernetesFastAPIAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Indore, Madhya Pradesh, India

Work mode:

Onsite

Published on:

13 August 2026

What they need


Role SummaryDesign, develop, deploy, and optimize enterprise AI/ML, Deep Learning, Computer Vision, and Generative AI solutions. Build scalable AI platforms, LLM applications, RAG systems, Agentic AI workflows, AI chatbots/copilots, and intelligent automation while ensuring performance, security, scalability, and production readiness.Key Responsibilities

  • Develop ML, Deep Learning, Computer Vision, and Generative AI applications.
  • Build LLM, RAG, AI chatbot/copilot, and Agentic AI solutions using LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, and MCP.
  • Fine-tune, evaluate, optimize, and deploy foundation models (LoRA/QLoRA, PEFT, Hugging Face, Ollama, vLLM, TensorRT-LLM).
  • Design scalable AI architectures, REST APIs, FastAPI/Flask microservices, Docker/Kubernetes deployments, and cloud-native solutions.
  • Develop Computer Vision, OCR, Intelligent Document Processing (IDP), object detection, segmentation, and document intelligence systems.
  • Build model training, inference, CI/CD, MLOps, monitoring, benchmarking, A/B testing, and production pipelines.
  • Collaborate with Product, Data Engineering, DevOps, and MLOps teams; mentor engineers and drive technical best practices.

Technical Skills

  • Programming: Python, SQL, Git, REST APIs
  • AI/ML: Supervised & Unsupervised Learning, Feature Engineering, Model Evaluation, Explainability, Time Series, Recommendation Systems
  • Deep Learning: TensorFlow, PyTorch, Hugging Face, CNN, RNN/LSTM/GRU, Transformers, Transfer Learning, Fine-tuning, Quantization
  • Generative AI: LLMs, Prompt Engineering, Embeddings, Function Calling, Context Engineering, Guardrails, AI Safety
  • RAG & Agentic AI: RAG, LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, MCP, AI Agents, Multi-Agent Systems, Tool Calling, Vector & Semantic Search
  • Computer Vision: OpenCV, YOLO, Detectron2, OCR (PaddleOCR, EasyOCR, Tesseract), Object Detection, Image Classification & Segmentation, Intelligent Document Processing (IDP)
  • Backend & APIs: FastAPI, Flask, Microservices, JWT/OAuth, Async APIs
  • Databases: PostgreSQL, MySQL, MongoDB, Redis, Pinecone, ChromaDB, FAISS, Weaviate, Milvus
  • Cloud Platforms: Azure (Azure OpenAI, Azure ML, AKS), AWS (Bedrock, SageMaker, ECS/EKS, Lambda), GCP (Vertex AI, Cloud Run, BigQuery)
  • DevOps & MLOps: Docker, Kubernetes, Helm, MLflow, CI/CD, GitHub Actions, GitLab CI, Azure DevOps, Jenkins, Model Registry, Model Monitoring

Soft SkillsStrong analytical and problem-solving skills, AI system design, performance optimization, debugging, stakeholder communication, mentoring, documentation, and Agile/Scrum collaboration.

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