Data Scientist - Artificial Intelligence/Machine Learning Models

Description:- Design, develop, and maintain backend services and APIs to support AI/ML applications at scale.- Productionize ML and deep learning models, ensuring efficiency, reliability, and low-latency inference.- Build scalable microservices and REST/gRPC APIs for deploying AI solutions in enterprise environments.- Optimize AI model serving using frameworks such as TensorRT, ONNX Runtime, Triton Inference Server, or FastAPI.- Implement MLOps practices including model versioning, monitoring, and automated deployments.- Collaborate with AI researchers, data scientists, and product managers to translate prototypes into production-ready systems.- Ensure robustness, fault tolerance, and security in backend AI systems.- Integrate AI services with enterprise data platforms, cloud systems, and third-party APIs.- Contribute to architecture discussions, design reviews, and performance tuning.- Mentor junior engineers and contribute to best practices in AI software engineering.Educational & Experience requirements :- Bachelors degree with at least 7 years of experience or Masters with at least 4 years of experience in Computer Science, Software Engineering, Data Science, or related fields.- Preferred to have degree from a Tier-1/2 institute (IIT/IISc/NITs if studied in India) or a globally top-ranked university (as per QS).Technical Requirements :- Strong proficiency in Python and backend frameworks (FastAPI).- Expertise in Prompt engineering and working with various LLMs.- Experience in productionizing AI/ML models with efficient inference pipelines.- Hands-on experience with model deployment frameworks (Triton, TensorRT, TorchServe, ONNX Runtime).- Knowledge of cloud platforms (Azure, GCP) and container technologies (Docker).- Strong experience with microservices architecture, CI/CD pipelines, and monitoring tools (Prometheus, Grafana).- Familiarity with databases (SQL/NoSQL) and scalable data storage solutions.- Exposure to LLMs, SLMs, and GenAI model integration into backend systems is a strong plus.- Understanding of security, authentication, and performance optimization in large-scale systems.- Experience with version control (Git) and Agile development practices.Behavioral Requirements:- Excellent problem-solving skills and attention to detail.- Strong written and verbal communication skills in English.- Ability to work collaboratively in cross-functional teams.- Passion for building reliable backend systems that bring AI models into real-world impact. (ref:hirist.tech) Description:- Design, develop, and maintain backend services and APIs to support AI/ML applications at scale.- Productionize ML and deep learning models, ensuring efficiency, reliability, and low-latency inference.- Build scalable microservices and REST/gRPC APIs for deploying AI solutions in enterprise environments.- Optimize AI model serving using frameworks such as TensorRT, ONNX Runtime, Triton Inference Server, or FastAPI.- Implement MLOps practices including model versioning, monitoring, and automated deployments.- Collaborate with AI researchers, data scientists, and product managers to translate prototypes into production-ready systems.- Ensure robustness, fault tolerance, and security in backend AI systems.- Integrate AI services with enterprise data platforms, cloud systems, and third-party APIs.- Contribute to architecture discussions, design reviews, and performance tuning.- Mentor junior engineers and contribute to best practices in AI software engineering.Educational & Experience requirements :- Bachelors degree with at least 7 years of experience or Masters with at least 4 years of experience in Computer Science, Software Engineering, Data Science, or related fields.- Preferred to have degree from a Tier-1/2 institute (IIT/IISc/NITs if studied in India) or a globally top-ranked university (as per QS).Technical Requirements :- Strong proficiency in Python and backend frameworks (FastAPI).- Expertise in Prompt engineering and working with various LLMs.- Experience in productionizing AI/ML models with efficient inference pipelines.- Hands-on experience with model deployment frameworks (Triton, TensorRT, TorchServe, ONNX Runtime).- Knowledge of cloud platforms (Azure, GCP) and container technologies (Docker).- Strong experience with microservices architecture, CI/CD pipelines, and monitoring tools (Prometheus, Grafana).- Familiarity with databases (SQL/NoSQL) and scalable data storage solutions.- Exposure to LLMs, SLMs, and GenAI model integration into backend systems is a strong plus.- Understanding of security, authentication, and performance optimization in large-scale systems.- Experience with version control (Git) and Agile development practices.Behavioral Requirements:- Excellent problem-solving skills and attention to detail.- Strong written and verbal communication skills in English.- Ability to work collaboratively in cross-functional teams.- Passion for building reliable backend systems that bring AI models into real-worl