AI/Machine Learning Engineer

2 weeks ago

Bengaluru, Karnataka, India Motiveminds Consulting Full time ₹ 12,00,000 - ₹ 36,00,000 per year

AI/Machine Learning Engineer (3-5 years)

Key Responsibities

  • Design, develop, and deploy machine learning / deep learning models for NLP, computer vision, or predictive analytics use cases.
  • Build and maintain end-to-end ML pipelines data preprocessing, feature engineering, model training, evaluation, and deployment.
  • Implement RAG, LangChain, and vector-based retrieval workflows using open-source or cloud LLMs.
  • Work with data scientists and backend teams to productionize models (APIs, Docker, CI/CD).
  • Optimize model performance using TensorRT, ONNX, quantization, and GPU acceleration.
  • Maintain experiment tracking, version control, and documentation (MLflow, DVC, Git).
  • Collaborate in Agile sprints, contribute to code reviews, and ensure reproducibility and scalability.

Technical Skills :

AreaTools Frameworks

Languages Python (core), SQL, Bash

ML / DL Scikit-learn, PyTorch, TensorFlow, Keras

Data Engineering Pandas, NumPy, Spark, HuggingFace Datasets

NLP Transformers, LangChain, OpenAI API, LLaMA, RAG pipelines

Computer Vision OpenCV, YOLO, Detectron2, Mask R-CNN

MLOps Docker, MLflow, FastAPI, REST APIs, GitHub Actions

Cloud / GPU Azure ML / AWS Sagemaker / GCP Vertex AI, CUDA, TensorRT

Databases PostgreSQL, MongoDB, FAISS, Pinecone

Versioning & Collaboration Git, JIRA / Trello, Confluence

  • Strong analytical and problem-solving mindset.
  • Eagerness to learn new AI frameworks and experiment rapidly.
  • Clear communication, documentation, and team collaboration abilities.
  • Ownership mindset ability to take POC to pilot independently.

Preferred Background

  • Bachelors or Masters in Computer Science, Data Science, or related field.
  • 35 years of experience in AI/ML or applied data science.
  • Exposure to LLM applications, RAG, or multimodal models is a plus.
  • Contributions to open-source AI projects or Kaggle competitions are value

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