AI/ML Engineer

About the Role

We at IDEA Foundation, we are seeking an experienced AI/ML Engineer to design, develop, and deploy intelligent systems that leverage machine learning and advanced analytics to solve complex business problems. The ideal candidate will work closely with cross-functional teams to build scalable AI solutions, develop robust ML models, and optimize data-driven decision-making across the organization.

Key Responsibilities:

AI/ML Model Development:

• Design, develop, train, and deploy machine learning and deep learning models to solve complex business challenges.
• Build scalable AI solutions that improve operational efficiency, customer experience, and data-driven decision making.
• Implement advanced algorithms for prediction, classification, recommendation systems, and ranking models.

Data Engineering & Pipeline Development:

• Build and maintain efficient data pipelines for data ingestion, transformation, and feature generation.
• Collect, clean, preprocess, and validate large datasets to ensure data quality and model reliability.
• Collaborate with data engineering teams to optimize data architecture for machine learning workflows.

Feature Engineering & Model Optimization:

• Perform advanced feature engineering to improve model performance and predictive accuracy.
• Select appropriate algorithms and modeling techniques based on business requirements and dataset characteristics.
• Optimize models through hyperparameter tuning, validation strategies, and performance evaluation.

Model Evaluation & Monitoring:

• Develop robust model evaluation frameworks using appropriate metrics and validation methods.
• Monitor model performance in production and implement continuous improvement and retraining strategies.
• Identify and resolve issues related to model drift, scalability, and system reliability.

Cross-Functional Collaboration:

• Collaborate with product, engineering, analytics, and business teams to define machine learning use cases and KPIs.
• Translate business requirements into scalable machine learning solutions.
• Provide technical guidance on AI strategy and best practices.

Deployment & MLOps:

• Deploy machine learning models into production environments ensuring scalability, reliability, and performance.
• Implement CI/CD pipelines and leverage MLOps practices for model lifecycle management.
• Work with cloud platforms to deploy and manage ML services.
• Build and maintain efficient data pipelines for data ingestion, transformation, and feature generation.
• Collect, clean, preprocess, and validate large datasets to ensure data quality and model reliability.
• Collaborate with data engineering teams to optimize data architecture for machine learning workflows.

Feature Engineering & Model Optimization:

• Perform advanced feature engineering to improve model performance and predictive accuracy.
• Select appropriate algorithms and modeling techniques based on business requirements and dataset characteristics.
• Optimize models through hyperparameter tuning, validation strategies, and performance evaluation.

Model Evaluation & Monitoring:

• Develop robust model evaluation frameworks using appropriate metrics and validation methods.
• Monitor model performance in production and implement continuous improvement and retraining strategies.
• Identify and resolve issues related to model drift, scalability, and system reliability.

Cross-Functional Collaboration:

• Collaborate with product, engineering, analytics, and business teams to define machine learning use cases and KPIs.
• Translate business requirements into scalable machine learning solutions.
• Provide technical guidance on AI strategy and best practices.

Deployment & MLOps:

• Deploy machine learning models into production environments ensuring scalability, reliability, and performance.
• Implement CI/CD pipelines and leverage MLOps practices for model lifecycle management.
• Work with cloud platforms to deploy and manage ML services.

Required Skills & QualificationsTechnical Skills:

• Strong programming skills in Python (preferred), Java, or C++.
• Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Keras.
• Experience with data structures, algorithms, and software architecture.
• Familiarity with MLOps tools, containerization (Docker), and workflow orchestration tools.
• Experience with ElasticSearch or similar search technologies.
• Strong experience with cloud platforms (AWS, Azure, or GCP) for ML deployment.

Machine Learning Expertise:

• Deep understanding of machine learning algorithms, statistics, and probability.
• Experience in building recommendation systems and ranking models using:
• Collaborative filtering
• Content-based filtering
• Deep learning approaches
• Reinforcement learning and bandit algorithms
• Experience with graph-based algorithms and graph databases.

NLP & Advanced AI:

• Practical experience with Natural Language Processing (NLP) techniques including:
• Tokenization
• Entity recognition
• Text classification
• Transformer-based models such as BERT, GPT, etc.

Experience:

• Minimum 3+ years of experience in AI/ML development or Machine Learning Engineering.
• Proven track record of building and deploying production-grade ML systems.

Education:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, or a related field.

Soft Skills:

• Excellent analytical and problem-solving skills.
• Strong communication and collaboration abilities.
• Ability to work effectively in cross-functional teams.
• Passion for continuous learning and innovation in AI technologies.

Pay: ₹1,200,000.00 - ₹1,500,000.00 per year

Ability to commute/relocate:

• Bengaluru, Karnataka: Reliably commute or planning to relocate before starting work (Required)

Application Question(s):

• Are you an immediate joiner? If not, please share your notice period and earliest date of availability.
• What is your current CTC ?
• What is your expected CTC?
• How many years of experience do you have as a AI/ML Engineer?

Experience:

• Aws: 3 years (Required)

Work Location: Hybrid remote in Bengaluru, Karnataka