Job Overview :
We are seeking a highly experienced Lead AI / ML Engineer to spearhead the design, development, and deployment of advanced AI and machine learning solutions. This role combines technical leadership with hands-on engineering expertise to build production-ready ML systems that deliver measurable business value. The ideal candidate will be a strategic thinker, an excellent mentor, and a skilled practitioner in machine learning, deep learning, and scalable AI architectures.
Key Responsibilities :
AI / ML Strategy & Leadership :
- Lead the end-to-end development of machine learning solutions, from ideation to deployment.
- Define the AI / ML roadmap and align with organizational goals.
- Mentor, guide, and upskill a team of AI / ML engineers and data scientists.
- Collaborate with product leaders, stakeholders, and executives to identify AI-driven opportunities.
Model Development & Deployment :
Design, train, validate, and optimize machine learning and deep learning models.Implement robust pipelines for data preprocessing, feature engineering, model training, and monitoring.Deploy ML models in production using MLOps best practices (CI / CD for ML, retraining pipelines).Ensure model scalability, interpretability, and fairness.System Design & Integration :
Architect scalable AI / ML solutions integrated with existing backend systems.Work with cloud platforms such as AWS, GCP, or Azure for distributed training and deployment.Build APIs and services to integrate AI / ML models into customer-facing applications.Research & Innovation :
Stay updated with the latest AI / ML research, frameworks, and technologies.Experiment with emerging tools and techniques to drive innovation.Publish or present findings to strengthen organizational thought leadership in AI.Qualifications and Skills :
Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or related field (PhD preferred).8 - 12 years of experience in AI / ML engineering, with at least 3 - 4 years in a leadership role.Strong proficiency in Python and ML / DL frameworks such as TensorFlow, PyTorch, or Keras.Hands-on experience with NLP, computer vision, recommendation systems, or generative AI models.Solid understanding of data engineering, ETL pipelines, and large-scale data processing.Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).Proficiency in MLOps practices and tools like MLflow, Kubeflow, Airflow, or Strong problem-solving, analytical, and communication skills.(ref : hirist.tech)