Role Summary :
We are seeking a Senior Advanced AI Engineer to design, develop, and deploy end-to-end AI / ML solutions that power next-generation intelligent and autonomous systems. The ideal candidate will be a hands-on technical leader who can build scalable AI architectures, optimize models, and establish best practices in MLOps, while mentoring junior team members in a full-stack AI / ML environment.
Key Responsibilities :
- Design and implement high-performance AI / ML models and workflows on cloud platforms such as Databricks, Vertex AI, or equivalent.
- Build and optimize MLOps pipelines using frameworks like MLflow or Kubeflow, integrating seamlessly with DevOps ecosystems.
- Evaluate models for performance, bias, and drift, and implement proactive mitigation strategies.
- Develop and integrate AI capabilities across Time Series, Computer Vision, NLP, and GenAI (RAG / Agentic AI) domains.
- Collaborate cross-functionally with Data Engineering, ML Engineering, and Product teams for scalable, production-ready deployments.
- Mentor and guide junior engineers, promoting excellence in ML development and best coding practices.
Preferred Competencies :
End-to-end AI / ML lifecycle expertise from data ingestion to deployment and monitoring.Strong analytical mindset with emphasis on data-driven decision-making.Hands-on experience with cloud platforms (AWS / Azure / GCP) for large-scale training and deployment.Excellent communication and documentation skills, with the ability to simplify complex concepts.Familiarity with Agile / Scrum & Experience :Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or related field.68 years of hands-on experience in developing and deploying machine learning models in production.Proven experience with TensorFlow, PyTorch, and modern MLOps practices (CI / CD, containerization, orchestration).Strong proficiency in Python; additional experience in Scala or Java is a plus.Why Join :
Opportunity to work on cutting-edge AI and GenAI projects with end-to-end ownership.Remote flexibility with a high-impact engineering culture.Exposure to modern AI stacks, model optimization, and production-grade ML architecture.(ref : hirist.tech)