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 workplace 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, LangC