Job Description : Engineer :
Position Overview :
We are looking for a skilled and innovative AI / ML Engineer to join our team. The ideal candidate will have experience in designing, developing, and deploying models, as well as a strong background in AI / ML and software engineering.
You will be responsible for building scalable AI solutions and integrating them into various applications, with a focus on generative AI techniques.
Key Responsibilities :
- Design, develop, and deploy machine learning models for a wide range of applications, including classification, regression, clustering, and time series forecasting systems.
- Skilled at researching and implementing solutions to address data analytics challenges, leveraging statistics, machine learning, and time series modelling.
- Demonstrates a strong understanding of generative AI concepts, coupled with hands-on experience in building robust workflows around Large Language Models (LLMs) using frameworks such as LangChain, LlamaIndex, and similar tools.
- Familiarity in designing and implementing Agentic AI workflows, enabling LLMs to autonomously plan, execute, and adapt multi-step tasks by leveraging external tools and systems.
- Utilize pre-trained models (e.g., GPT, Llama etc) and fine-tune them for specific applications, such as question answering, summarization, and text generation.
- Develop and maintain pipelines for automated model training, validation, and deployment.
- Work with cross-functional teams to integrate AI / ML models into production systems, whether on-premises or cloud-based, ensuring seamless operation and scalability.
- Document model development processes and create clear, concise reports for stakeholders
Required Skills :
Strong programming skills in Python, with experience in libraries such as Scikit-learn, Pandas, TensorFlow and PyTorch.Expertise in machine learning algorithms and statistics.Extensive experience with generative AI models and frameworks, including working with large pre-trained language models like LLama , mixtral, claude,etc and deploying custom LLMs for specific tasks.Familiarity with on-premises and cloud platforms for deploying and scaling machine learning models.Knowledge of MLOps practices, including CI / CD pipelines and containerization.Proficiency in SQL for data querying, manipulation, and analysis.Familiarity with version control systems (e.g., Git) and collaborative development workflows.(ref : hirist.tech)