The Family Office Company logo
Full-time
Remote friendly (Bangalore, Karnataka, India)
India

Role Overview We are looking for:

An experienced AI Engineer to develop and deploy machine learning solutions that drive business impact. You will manage projects from data preparation to model deployment, collaborating with cross-functional teams. Ideal candidates are passionate about AI, skilled in solving complex problems, and able to turn research into practical applications. 

Key Responsibilities:

• Model Development: Design, train, and implement robust machine learning and AI models for production use. 

• Data Engineering: Collect, clean, and structure diverse data sources to enable high-quality model training. 

• Optimization & Evaluation: Rigorously test, evaluate, and fine-tune models for accuracy, performance, and scalability. 

• Deployment & MLOps: Deploy AI models into production environments, automate workflows, and ensure reliable performance with monitoring systems. • Collaboration: Partner with product managers, data engineers, and domain experts to translate business needs into AI-driven solutions. 

• Innovation & Research: Stay ahead of AI trends, experiment with new techniques, and bring innovative ideas into practice. 

• Documentation: Clearly document methodologies, experiments, and system designs for knowledge sharing and reproducibility. 

Requirements:

• Bachelor’s or master’s degree in computer science, Engineering, Data Science, or a related field.

    • Strong proficiency in Python (or similar languages such as Java, C++, or R). 

    • Hands-on experience with ML/DL frameworks such as TensorFlow, PyTorch, or Scikit-learn. 

    • Solid foundation in statistics, algorithms, and data structures. 

    • Proven ability to work with large, complex datasets and build scalable data pipelines. 

    • Excellent problem-solving, analytical thinking, and communication skills. Preferred Qualifications 

    • Experience in deep learning, NLP, or computer vision. 

    • Knowledge of MLOps practices (CI/CD for ML, model versioning, monitoring). 

    • Familiarity with cloud AI/ML services (AWS, Azure ML, GCP). 

    • Contributions to open-source projects or publications in applied AI.