AI /Ml Lead engineer

Company Description Better Analytics is a data-driven technology company focused on transforming complex information into actionable insights. Through the Scremer platform, Better Analytics helps organizations understand and optimize their performance, brand presence, and customer engagement. The company emphasizes innovation in analytics, leveraging modern AI and machine learning techniques to deliver intelligent, scalable solutions. Team members collaborate across disciplines to build tools that are intuitive, reliable, and impactful for a wide range of clients.

Role Description The AI/ML Lead Engineer role at Better Analytics is a full-time on-site position based in Hyderabad. This role is responsible for designing, implementing, and optimizing machine learning models and AI systems that power the Scremer platform and related analytics products. Day-to-day tasks include leading end-to-end ML solution development, from problem definition and data exploration to model training, evaluation, deployment, and monitoring in production environments. The AI/ML Lead Engineer will collaborate closely with data engineers, product managers, and other stakeholders to translate business requirements into technical solutions, define AI roadmaps, and ensure system scalability and reliability. The role also involves mentoring team members, establishing best practices in ML engineering, and staying current with advancements in AI/ML to continuously improve the technology stack.

Qualifications

• Strong foundation in Computer Science and Algorithms, with experience designing efficient, scalable solutions.
• Proficiency in Pattern Recognition and Neural Networks, including hands-on work with deep learning frameworks.
• Solid understanding of Statistics and probabilistic modeling for data analysis, inference, and model evaluation.
• Experience leading AI/ML projects end-to-end, from data preparation to deployment and performance optimization.
• Advanced programming skills in languages commonly used for ML (e.g., Python), and familiarity with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with data pipelines, model serving, and MLOps practices on cloud or distributed computing environments.
• Ability to communicate complex technical concepts clearly to technical and non-technical stakeholders and to mentor junior team members.
• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related quantitative field, or equivalent practical experience.