Job purpose:
This role is responsible for designing, developing, and deploying advanced AI/ML and Generative AI solutions to solve complex business problems. The position focuses on building scalable machine learning models and pipelines while enabling data-driven decision-making across the organization.
Responsibilities:
- Advanced Data Analysis: Go beyond basic data exploration and delve into complex statistical analysis and modelling techniques using Python libraries like scikit-learn and TensorFlow. Conduct exploratory data analysis to gain insights and inform modelling decisions.
- Machine Learning Expertise: Architect and implement sophisticated machine learning models to solve real-world and complex problems. Design and implement scalable machine learning pipelines and workflows.
- Communication & Collaboration: Effectively translate technical findings into clear and actionable insights for technical and non-technical stakeholders. Collaborate with business teams to ensure data-driven solutions align with business objectives
- Mentorship & Knowledge Sharing: Guide and mentor junior engineers, fostering a collaborative learning environment and sharing best practices within the team. Stay updated with the latest advancements in machine learning research and apply them to improve our solutions.
Skills:
- Bachelor’s degree in computer science, Data Science, AI, or a related field
- 1+ years of hands-on experience in AI/ML projects (including internships or academic projects)
- Proficiency in Python and familiarity with ML libraries such as scikit-learn, TensorFlow, PyTorch, or Hugging Face
- Basic understanding of machine learning concepts, evaluation metrics, and data preprocessing techniques
- Experience with MLOps tools such as MLflow or Vertex AI
- Exposure to cloud platforms (AWS, Azure, or GCP)
- Familiarity with version control tools such as Git
- Experience with Jupiter notebooks, APIs, and basic deployment workflows
- Exposure to GenAI tools and frameworks such as OpenAI, LangChain, or vector databases
- Strong analytical and problem-solving skills
- Ability to work in a collaborative and fast-paced environment
- Strong communication skills
- Exposure to production-level AI deployments
- Understanding of model monitoring and optimization techniques
