Machine Learning Engineer

23 hours ago

Ahmedabad, Gujarat, India Ace Infoway Pvt. Ltd. Full time ₹ 15,00,000 - ₹ 25,00,000 per year

About The Role
We are seeking highly experienced Senior Machine Learning Engineers to join our AI team. Candidates should have 4+ years of experience building and deploying production-grade ML models. You will be responsible for end-to-end ML solutions, data-driven projects, and creating scalable, high-performance AI systems.

Key Responsibilities

  • Design, develop, and deploy machine learning and deep learning models.
  • Conduct advanced data preprocessing, feature engineering, and model evaluation.
  • Implement optimization techniques for algorithm performance and scalability.
  • Work with Python frameworks such as Scikit-learn, TensorFlow, PyTorch, and Keras for model development.
  • Build interactive dashboards using Streamlit, Plotly, and other visualization tools.
  • Collaborate with cross-functional teams including data engineering, product, and software development.
  • Research and implement state-of-the-art ML/AI algorithms.
  • Deploy models using FastAPI, Flask, Docker, or Kubernetes.
  • Monitor and maintain production models for performance and reliability.

Required Skills & Expertise

  • Programming Languages : Python (NumPy, Pandas, Matplotlib, Seaborn, etc.), SQL.
  • Machine Learning : Supervised & unsupervised learning, regression, classification, clustering, recommendation systems, ensemble methods, Scikit-learn.
  • Deep Learning : CNNs, RNNs, LSTMs, GRUs, Transformers, attention mechanisms, TensorFlow, PyTorch, Keras.
  • Natural Language Processing (NLP) : Text preprocessing, embeddings, transformers (BERT, GPT), sentiment analysis, NER.
  • Computer Vision : Image classification, object detection, segmentation.
  • Time Series Analysis : Forecasting using ARIMA, Prophet, LSTM, RNN.
  • Algorithms & Data Structures : Strong foundation in algorithm design, complexity analysis, probability, statistics, and optimization.
  • MLOps / Deployment : FastAPI/Flask, Docker, Kubernetes, CI/CD pipelines, cloud deployment (AWS/GCP/Azure).
  • Data Management : SQL, NoSQL, ETL pipelines, big data frameworks (Spark, Hadoop).
  • Visualization & Reporting : Streamlit, Plotly, Matplotlib, Seaborn, interactive dashboards.

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