Machine Learning Engineer

This role is for one of Weekday’s clients
Salary range: Rs 1000000 - Rs 2700000 (ie INR 10 - 27 LPA)

Min Experience: 6+ years
Location: Pune, Maharashtra, India
JobType: full-time

We are looking for an experienced and highly skilled Machine Learning Engineer with 6–10 years of experience in building, deploying, and scaling machine learning solutions for real-world business problems. The ideal candidate will have strong expertise in Machine Learning and Data Science, with a proven ability to work across the complete lifecycle of ML projects—from data preparation and model development to deployment, monitoring, and optimization.

You will collaborate closely with data scientists, software engineers, product teams, and business stakeholders to translate complex requirements into reliable, scalable, and production-ready machine learning solutions.

Requirements

Key Responsibilities

• Design, develop, train, and deploy machine learning models for classification, regression, clustering, recommendation, forecasting, and other business use cases.
• Apply advanced machine learning techniques to solve complex problems and improve model accuracy, scalability, and performance.
• Analyze large and complex datasets to identify trends, patterns, relationships, and actionable insights.
• Perform data preprocessing, feature engineering, feature selection, exploratory data analysis, and statistical analysis.
• Build robust data pipelines and prepare high-quality datasets for machine learning and analytical applications.
• Evaluate models using appropriate metrics, validation techniques, and experimentation frameworks.
• Optimize existing models and algorithms to improve accuracy, latency, scalability, and computational efficiency.
• Deploy machine learning models into production environments and ensure their reliability and maintainability.
• Monitor model performance and identify issues such as data drift, model degradation, and prediction inconsistencies.
• Collaborate with software engineers to integrate ML models into scalable applications, APIs, and production systems.
• Conduct experiments, A/B tests, and hypothesis-driven analysis to evaluate new approaches.
• Stay updated with developments in machine learning, artificial intelligence, data science, and emerging modeling techniques.
• Document methodologies, experiments, models, and technical decisions for effective knowledge sharing.

Must-Have Skills

• Strong hands-on expertise in Machine Learning and Data Science.
• 6–10 years of professional experience in machine learning, data science, or a closely related field.
• Strong understanding of supervised and unsupervised learning algorithms.
• Proficiency in Python and commonly used machine learning and data science libraries such as Scikit-learn, Pandas, NumPy, and SciPy.
• Strong knowledge of statistics, probability, optimization, and mathematical foundations of machine learning.
• Experience with feature engineering, model selection, hyperparameter tuning, and model evaluation.
• Strong SQL skills and experience working with large datasets.
• Experience taking machine learning models from experimentation to production deployment.
• Understanding of ML lifecycle, model monitoring, versioning, and performance optimization.
• Strong analytical and problem-solving skills with the ability to translate business problems into machine learning solutions.

Good to Have

• Experience with deep learning frameworks such as TensorFlow or PyTorch.
• Exposure to NLP, recommendation systems, computer vision, time-series forecasting, or generative AI.
• Experience working with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with Docker, Kubernetes, MLflow, CI/CD, and MLOps practices.
• Experience working with distributed data processing technologies such as Spark.