About Company
where innovation meets transformation. We are strategists, designers, & technologists. We specialize in crafting tailored IT solutions and digital strategies that advance businesses to excel & drive real time benefits in today's fast-paced, technology-driven world. From advisory to robust e-commerce platform implementation, our expertise ensures seamless digital experiences that drive growth and elevate your brand. At Commergence, we don't just create solutions we shape the future.
Job Description
- Deliver end-to-end AI solutions by designing, training, and deploying Machine Learning models and AI systems
- Collaborate with cross-functional teams including backend/frontend engineers, product managers and contribute to architectural decisions.
- Preprocess and analyse large datasets from structured and unstructured sources.
- Develop data pipelines and model training infrastructure.
- Optimize model performance and scalability in production environments.
- Implement CI/CD workflows for model versioning and deployment.
- Assess and apply adoption of low-/no-code platforms like Copilot Studio to accelerate AI solution delivery and integrate with existing ML systems.
- Understand cloud-native architecture concepts and have knowledge of best practices for high availability, scalability, resilience, performance, and security requirements in the cloud.
- Stay current with industry trends and academic research to integrate state-of-the-art techniques.
- Ensure compliance with data security, data privacy regulations and ethical AI practices.
Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or related fields
- 5+ years of experience in AI/ML engineering or applied machine learning.
- Proficiency in Python, with knowledge of ML libraries
- Experience with deep learning frameworks (e.g. TensorFlow)
- Strong knowledge of data structures, algorithms, and software engineering principles.
- Experience with cloud platforms (Azure, AWS) and ML ops tools (e.g. Azure Machine Learning, MLflow)
- Familiarity with containerization and orchestration (Docker, Kubernetes)
- Proficiency in RESTful API development and strong understanding of SQL and relational database design.
- Demonstrated problem-solving ability, with a proactive mindset and eagerness to continuously learn new technologies
- Knowledge of regulatory and security considerations when delivering AI-enabled digital services
- Effective communication skills, able to explain technical concepts to non-technical stakeholders.
- Collaborative mindset and willingness to mentor or guide team members
Desirable Experience & Skills
- Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
- Experience in end-to-end AI solution lifecycle: problem definition, data collection, model development, deployment, and monitoring.
- Work on scalable AI/ML projects across company functions and technical domains such as NLP, computer vision, predictive analytics, or recommendation systems.
- Contributions to open-source AI projects or research publications.
- Experienced in AI/ML strategy, technology selection, and model governance standards.
- Experienced in Agile development cycles and DevOps practices
Skills: machine learning,ai,cloud
