AI/ML Engineer

Job Description: AI/ML 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