AI/ML Engineer

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟭𝟬𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟯𝟴𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟭𝟬-𝟯𝟴 𝗟𝗣𝗔)

Experience: 6+ yrs

Location: Pune, Maharashtra, India

Job Type: Full-time

We are looking for an experienced AI/ML Engineer with 6+ years of experience in Artificial Intelligence, Machine Learning, and Data Science to design, develop, and deploy intelligent, scalable, and production-ready solutions. The role combines strong data science expertise with practical machine learning engineering to solve complex business and technical problems.

The ideal candidate will have a strong understanding of the complete machine learning lifecycle, from data exploration and feature engineering to model development, evaluation, deployment, and monitoring. You will work closely with engineering, product, data, and business teams to transform data into reliable AI-driven solutions and measurable business outcomes.

Requirements

Key Responsibilities

• Design, develop, test, and deploy Artificial Intelligence and Machine Learning solutions for complex business problems.
• Apply Data Science techniques to analyze structured and unstructured datasets and generate actionable insights.
• Perform exploratory data analysis to identify trends, patterns, correlations, anomalies, and opportunities.
• Develop supervised and unsupervised machine learning models for classification, regression, clustering, forecasting, recommendation, and other use cases.
• Perform data preprocessing, feature engineering, feature selection, model training, tuning, and validation.
• Select appropriate algorithms, evaluation metrics, and experimentation approaches based on business and technical requirements.
• Build reusable and scalable machine learning pipelines for experimentation and production deployment.
• Collaborate with Data Engineers to define data requirements and develop reliable data-processing workflows.
• Work with Software Engineers to integrate ML models into production applications, APIs, and business systems.
• Evaluate model performance and continuously improve accuracy, scalability, reliability, and efficiency.
• Monitor deployed models and identify issues related to model drift, data quality, performance, or reliability.
• Apply appropriate practices for model documentation, reproducibility, data quality, and governance.
• Conduct experiments and communicate findings, model performance, and business impact to technical and non-technical stakeholders.
• Troubleshoot complex AI/ML issues and perform root-cause analysis across data, models, and production systems.
• Contribute to automation, MLOps, CI/CD, model deployment, and monitoring initiatives.
• Stay current with emerging Artificial Intelligence, Machine Learning, and Data Science technologies, frameworks, and best practices.
• Mentor junior engineers and contribute to technical standards, knowledge sharing, and continuous improvement.

What Makes You a Great Fit

• 6+ years of professional experience in Artificial Intelligence, Machine Learning, Data Science, AI/ML Engineering, or a closely related field.
• Strong hands-on experience developing and deploying Machine Learning models in real-world or production environments.
• Strong understanding of Data Science fundamentals

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  , including exploratory data analysis, statistics, feature engineering, experimentation, and model evaluation.
• Strong programming skills in Python and experience with libraries such as NumPy, Pandas, Scikit-learn, or equivalent frameworks.
• Good understanding of supervised and unsupervised learning, statistical modeling, predictive analytics, and model optimization.
• Experience with deep learning frameworks such as PyTorch or TensorFlow is an advantage.
• Strong SQL skills and experience working with relational, analytical, or large-scale datasets.
• Experience building data-processing and machine learning pipelines.
• Familiarity with MLOps, model deployment, monitoring, Docker, Kubernetes, CI/CD, or cloud platforms is desirable.
• Strong understanding of model performance, scalability, reliability, data quality, and production readiness.
• Ability to translate business requirements into practical AI and Machine Learning solutions.
• Strong analytical, problem-solving, and critical-thinking skills.
• Excellent communication skills with the ability to explain complex technical and data concepts clearly.
• Ability to work independently while collaborating effectively with Product, Engineering, Data, and Business teams.
• Experience mentoring engineers or contributing to technical leadership is an advantage.
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or a related discipline is preferred.