Machine Learning / AI Engineer

About the Role:

Machine Learning / AI Engineer

Location:

Key Responsibilities:

• Design, develop, and deploy machine learning models to solve complex business problems
• Work across the full ML lifecycle: data collection, preprocessing, model training, evaluation, deployment, and monitoring
• Collaborate with data engineers, product managers, and software engineers to integrate ML models into production systems
• Conduct research and stay up-to-date with the latest ML/AI advancements, applying them where appropriate
• Optimize models for performance, scalability, and robustness
• Document methodologies, experiments, and findings clearly for both technical and non-technical audiences
• Mentor junior ML engineers or data scientists as needed

Required Qualifications:

• Bachelors or Masters degree in Computer Science, Machine Learning, Data Science, or related field (Ph.D. is a plus)
• Minimum of 5 hands-on ML/AI projects, preferably in production or with real-world datasets
• Proficiency in Python and ML libraries/frameworks like TensorFlow, PyTorch, Scikit-learn, XGBoost
• Solid understanding of core ML concepts: supervised/unsupervised learning, neural networks, NLP, computer vision, etc.
• Experience with model deployment using APIs, containers (Docker), cloud platforms (AWS/GCP/Azure)
• Strong data manipulation and analysis skills using Pandas, NumPy, and SQL
• Knowledge of software engineering best practices: version control (Git), CI/CD, unit testing

Preferred Skills:

• Experience with MLOps tools (MLflow, Kubeflow, SageMaker, etc.)
• Familiarity with big data technologies like Spark, Hadoop, or distributed training frameworks
• Experience working in Fintech environments would be a plus
• Strong problem-solving mindset with excellent communication skills
• Experience in working with vector database.
• Understanding of RAG vs Fine-tuning vs Prompt Engineering

Why Join Us:

• Work on impactful, real-world AI challenges
• Collaborate with a passionate and innovative team
• Opportunities for career advancement and learning
• Flexible work environment (remote/hybrid options)
• Competitive compensation and benefits