Machine Learning Engineer

Job Description: Role Overview: As a fresher ML Engineer at Dhan AI, you will collaborate with experienced data scientists and ML engineers to participate in building, training, and deploying machine learning models. You will gain hands-on experience throughout the entire ML lifecycle, starting from data wrangling to deploying models into production. Key Responsibilities: - Assist in building and evaluating ML/DL models for various business use cases - Conduct exploratory data analysis (EDA) and feature engineering on real datasets - Write clean and efficient Python code for data pipelines and model training - Experiment with different algorithms and systematically track results - Collaborate with the engineering team to deploy models into production - Stay updated with the latest research and contribute relevant ideas to the team Qualifications Required: - Strong foundation in Python and its data ecosystem (NumPy, Pandas, Scikit-learn) - Understanding of core ML concepts such as regression, classification, clustering, and model evaluation - Familiarity with at least one deep learning framework (TensorFlow or PyTorch) - Basic knowledge of statistics and probability - Comfortable working with data, including cleaning, transforming, and visualizing it - Familiarity with Git and version control - Good to have experience with NLP, computer vision, or time series problems - Exposure to MLOps tools like MLflow, DVC, or similar - Familiarity with cloud ML services such as AWS SageMaker, GCP Vertex AI, etc. - Knowledge of SQL and experience working with structured data - Prior internship or project experience with real datasets (Note: Omitted additional details of the company as it was not present in the provided job description) Job Description: Role Overview: As a fresher ML Engineer at Dhan AI, you will collaborate with experienced data scientists and ML engineers to participate in building, training, and deploying machine learning models. You will gain hands-on experience throughout the entire ML lifecycle, starting from data wrangling to deploying models into production. Key Responsibilities: - Assist in building and evaluating ML/DL models for various business use cases - Conduct exploratory data analysis (EDA) and feature engineering on real datasets - Write clean and efficient Python code for data pipelines and model training - Experiment with different algorithms and systematically track results - Collaborate with the engineering team to deploy models into production - Stay updated with the latest research and contribute relevant ideas to the team Qualifications Required: - Strong foundation in Python and its data ecosystem (NumPy, Pandas, Scikit-learn) - Understanding of core ML concepts such as regression, classification, clustering, and model evaluation - Familiarity with at least one deep learning framework (TensorFlow or PyTorch) - Basic knowledge of statistics and probability - Comfortable working with data, including cleaning, transforming, and visualizing it - Familiarity with Git and version control - Good to have experience with NLP, computer vision, or time series problems - Exposure to MLOps tools like MLflow, DVC, or similar - Familiarity with cloud ML services such as AWS SageMaker, GCP Vertex AI, etc. - Knowledge of SQL and experience working with structured data - Prior internship or project experience with real datasets (Note: Omitted additional details of the company as it was not present in the provided job description)