Job Tittle: ML engineer
Location: Pune
Experience: 3+ years
Looking for immediate joiners
Job Description:
We are seeking a passionate and skilled Machine Learning Engineer / ML Developer with 3+ years of hands-on experience in designing, developing, and deploying ML models. The ideal candidate should have a strong understanding of data science concepts, end-to-end ML pipelines, and production-level model integration.
Key Responsibilities:
- Design, build, and deploy machine learning and deep learning models for real-world applications.
- Perform data preprocessing, feature engineering, and exploratory data analysis (EDA).
- Develop and optimize ML pipelines for scalability and performance.
- Work with cross-functional teams to integrate ML models into production systems.
- Evaluate model performance using appropriate metrics and fine-tune algorithms.
- Implement model monitoring and retraining strategies for continuous improvement.
- Collaborate on research, experimentation, and PoC development for AI-driven initiatives.
Required Skills & Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
- Minimum 3 years of experience in ML / AI model development and deployment.
- Strong proficiency in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn, XGBoost, pandas, NumPy.
- Hands-on experience with data preprocessing, feature selection, and model evaluation.
- Experience in API development (Flask/FastAPI) for serving ML models.
- Knowledge of SQL/NoSQL databases, and cloud platforms (AWS, Azure, or GCP).
- Familiarity with MLOps tools like Docker, MLflow, or Kubernetes is a plus.
- Excellent problem-solving and analytical skills.
Nice to Have:
- Experience with NLP, Computer Vision, or Time Series Forecasting.
- Exposure to Deep Learning architectures (CNNs, RNNs, Transformers).
- Contributions to open-source ML projects or participation in Kaggle competitions.
Job Type: Full-time
Pay: ₹1,500,000.00 - ₹2,000,000.00 per year
Experience:
- ML Developer: 3 years (Preferred)
Work Location: In person