Key Responsibilities:
AI Solution Development:
- Develop and deploy AI models and algorithms to automate internal processes, enhance decision-making, and improve productivity.
- Build and fine-tune natural language processing (NLP) solutions for use cases such as document processing, chatbot development, and proactive insights.
- Create machine learning pipelines for predictive analytics and anomaly detection in operational workflows.
Integration and Deployment:
- Integrate AI models into existing internal applications, including CRM platforms, CLM systems, Employee-facing tools, Enterprise applications, Analytics tools and other custom inbuilt applications.
- Collaborate with DevOps teams to ensure efficient CI/CD pipelines for AI solutions.
Collaboration and Stakeholder Engagement:
- Partner with business stakeholders to identify pain points and opportunities for AI-driven enhancements.
- Work closely with IT and application development teams to align AI initiatives with organizational goals.
Data Management and Analysis:
- Leverage structured and unstructured data from multiple sources to train, test, and validate AI models.
- Implement data preprocessing pipelines to ensure data quality and completeness.
Performance Monitoring and Optimization:
- Continuously monitor and evaluate the performance of deployed AI models, ensuring accuracy, scalability, and efficiency.
- Optimize algorithms and infrastructure to reduce latency and improve user experience.
Innovation and Prototyping:
- Stay up-to-date with the latest trends and advancements in AI and machine learning to recommend and implement cutting-edge technologies.
- Rapidly prototype solutions for new business use cases, presenting proof-of-concept models to stakeholders.
Qualifications:
Education:
- Bachelor s or Master s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
Experience:
- 3 5 years of experience in AI engineering, machine learning, or data science roles.
- Proven track record of developing and deploying AI solutions in enterprise environments.
- Experience with CRM systems and automation platforms is a plus.
Technical Skills:
- Proficiency in programming languages like Python, R, or Java.
- Experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, etc.) and NLP libraries (SpaCy, Hugging Face, NLTK, etc.).
- Hands-on experience with cloud platforms (AWS, Azure, GCP) and AI tools (SageMaker, Vertex AI).
- Familiarity with APIs, microservices, and RESTful architectures.
- Strong understanding of data engineering concepts, including ETL pipelines and database management (SQL, NoSQL).
Soft Skills:
- Strong problem-solving and critical-thinking skills
- Excellent communication and collaboration abilities.
- Ability to work in a fast-paced environment and manage multiple priorities effectively
