Design, build, and deploy AI and machine learning solutions that solve real business problems.
Support the full AI development lifecycle, including data preparation, feature engineering, model training, validation, and optimization.
Develop and enhance scalable AI models using modern ML frameworks and cloud-based platforms.
Deploy, monitor, and maintain AI solutions in production to ensure performance, reliability, and scalability.
Collaborate with AI leads, engineers, and cross-functional stakeholders to translate business requirements into technical solutions.
Partner with onshore and offshore teams to support timely delivery of prioritized AI initiatives.
Apply security, data privacy, and compliance best practices throughout the development and release process.
Contribute to shared AI components, reusable assets, and development standards.
Stay current with emerging AI technologies and incorporate relevant advancements into solutions.
Support knowledge sharing by mentoring or enabling team members on AI tools and best practices.
Education:
Bachelor's degree in computer science, Engineering, Information Technology, Mathematics, Statistics, Physics, or a related field
Nice to have: Master's or Ph.D. in a relevant field.
Nice to have: Industry certifications in AI, machine learning, or cloud platforms.
Experience:
3+ years of experience developing and deploying AI / machine learning solutions.
Demonstrated experience deploying AI systems into production environments.
Experience collaborating with cross-functional teams to translate business requirements into scalable AI solutions.
Experience mentoring, training, or enabling other developers, analysts, or business users on AI tools, models, or best practices.
Core Technical Skills:
Strong proficiency in Python for AI and machine learning development
Hands-on experience with ML frameworks and libraries such as PyTorch, TensorFlow, and scikit-learn.
Experience with NLP and document-centric AI, including OCR and document processing, Document classification and entity extraction, Text summarization
Solid experience with data preprocessing, feature engineering, and analysis using tools such as: Pandas, NumPy, Matplotlib, Seaborn
Experience working with cloud-based AI platforms, preferably Microsoft Azure or AWS
Proficiency in SQL and experience with relational and/or NoSQL databases
Familiarity with containerization technologies such as Docker and/or Kubernetes
Familiary with building LLM-based solutions: Chatbots and conversational AI, Prompt engineering and evaluation, Retrieval-Augmented Generation (RAG), Intelligent or semantic search
Exposure to MLOps practices, including CI/CD pipelines for ML models, Model versioning, deployment automation, and monitoring.
Familiarity with REST API development and integrating AI capabilities into backend systems.
Experience contributing to shared AI components, development standards, or reference architectures.
Ways of Working:
Experience working in Agile and/or Waterfall delivery environments.
Experience collaborating with onshore and offshore teams.
Strong communication skills, including the ability to explain AI concepts and trade-offs to non-technical stakeholders.
