Job Description
Company Description
Join With is dedicated to empowering organizations by delivering deep market insights and tailored strategies designed to meet diverse business needs and budgets. Our comprehensive services include Political Management, Political Social Media, Advertisement, Customized Application Development, Data Analytics solutions, Custom BI Applications, Big Data Services, Data Storage, and Data Engineering. With an emphasis on making clients’ lives easier, we provide value-added solutions that foster growth and enhance business operations. Join With is committed to innovation and helping clients achieve sustainable success.
Role Description
This is a full-time, on-site role based in Nagpur for a Senior Machine Learning Engineer. As a senior strong foundations in machine learning and deep learning to build, fine-tune, and deploy ML models from scratch. This role is not focused on LLMs, prompt engineering, or Gen AI. Instead, the emphasis is on ML algorithms, feature engineering, model optimization, and production ML systems. The ideal candidate will have hands-on expertise on building, deploying, and scaling AI/ML solutions in production environments.
Experience: 5+ years working with ML / DL Algorithms.
Placement Type: Full Time Permanent position.
Key Responsibilities:
- Design, build, train, and fine-tune machine learning models using traditional ML and deep learning techniques
- Work on supervised, unsupervised, and semi-supervised learning problems
- Perform feature engineering, feature selection, and data preprocessing on structured and semi-structured data
- Implement and optimize models such as: Linear / Logistic Regression
- Decision Trees, Random Forest, Gradient Boosting (XGBoost, Light GBM, Cat Boost)
- SVM, k-NN, Naive Bayes
- Time-series and forecasting models (ARIMA, Prophet, LSTM if applicable)
- Build and fine-tune deep learning models (CNNs, RNNs, LSTMs, GRUs) where required
- Evaluate models using appropriate metrics and improve performance through hyperparameter tuning
- Deploy models into production and monitor performance, drift, and retraining needs
- Collaborate with data engineers, product, and business teams to translate requirements into ML solutions.
Qualifications
- BE/B. Tech – B. E or B. Tech – Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- Excellent problem-solving and critical thinking abilities.
- Experience with end-to-end deployment of AI/ML pipelines in production.
- Experience with Forecasting Models, churn Prediction, Sentiment Analysis, Fraud Detection.
Required Technical Skills :
- Backend & Frameworks : Node.js / Python / R, Graph QL, Apache Spark, Airflow, Hive
- Databases: Mongo DB, My SQL / SQL Server / Postgre SQL, No SQL
- API Development: Fast API, RESTful services.
- Dev Ops: Kubernets, Docker, CI/CD pipelines.
Machine Learning and AI:
• Tensor Flow, Py Torch, Scikit-learn, Hugging Face Transformers
• ML algorithms : classification, regression, clustering, etc.
• NLP / NLU / NLG techniques
• Libraries : Pandas, Num Py, XGBoost, Light GBM, Keras
• Development Tools : Jupyter Notebook, VS Code, Git
• Operating Systems : Windows, Ubuntu, Linux
Join With is dedicated to empowering organizations by delivering deep market insights and tailored strategies designed to meet diverse business needs and budgets. Our comprehensive services include Political Management, Political Social Media, Advertisement, Customized Application Development, Data Analytics solutions, Custom BI Applications, Big Data Services, Data Storage, and Data Engineering. With an emphasis on making clients’ lives easier, we provide value-added solutions that foster growth and enhance business operations. Join With is committed to innovation and helping clients achieve sustainable success.
Role Description
This is a full-time, on-site role based in Nagpur for a Senior Machine Learning Engineer. As a senior strong foundations in machine learning and deep learning to build, fine-tune, and deploy ML models from scratch. This role is not focused on LLMs, prompt engineering, or Gen AI. Instead, the emphasis is on ML algorithms, feature engineering, model optimization, and production ML systems. The ideal candidate will have hands-on expertise on building, deploying, and scaling AI/ML solutions in production environments.
Experience: 5+ years working with ML / DL Algorithms.
Placement Type: Full Time Permanent position.
Key Responsibilities:
- Design, build, train, and fine-tune machine learning models using traditional ML and deep learning techniques
- Work on supervised, unsupervised, and semi-supervised learning problems
- Perform feature engineering, feature selection, and data preprocessing on structured and semi-structured data
- Implement and optimize models such as: Linear / Logistic Regression
- Decision Trees, Random Forest, Gradient Boosting (XGBoost, Light GBM, Cat Boost)
- SVM, k-NN, Naive Bayes
- Time-series and forecasting models (ARIMA, Prophet, LSTM if applicable)
- Build and fine-tune deep learning models (CNNs, RNNs, LSTMs, GRUs) where required
- Evaluate models using appropriate metrics and improve performance through hyperparameter tuning
- Deploy models into production and monitor performance, drift, and retraining needs
- Collaborate with data engineers, product, and business teams to translate requirements into ML solutions.
Qualifications
- BE/B. Tech – B. E or B. Tech – Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- Excellent problem-solving and critical thinking abilities.
- Experience with end-to-end deployment of AI/ML pipelines in production.
- Experience with Forecasting Models, churn Prediction, Sentiment Analysis, Fraud Detection.
Required Technical Skills :
- Backend & Frameworks : Node.js / Python / R, Graph QL, Apache Spark, Airflow, Hive
- Databases: Mongo DB, My SQL / SQL Server / Postgre SQL, No SQL
- API Development: Fast API, RESTful services.
- Dev Ops: Kubernets, Docker, CI/CD pipelines.
Machine Learning and AI:
• Tensor Flow, Py Torch, Scikit-learn, Hugging Face Transformers
• ML algorithms : classification, regression, clustering, etc.
• NLP / NLU / NLG techniques
• Libraries : Pandas, Num Py, XGBoost, Light GBM, Keras
• Development Tools : Jupyter Notebook, VS Code, Git
• Operating Systems : Windows, Ubuntu, Linux
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