Job Description
<p><p><b>Role : </b> Associate Architect Machine Learning (Gen AI)<br/><br/><b>Experience : </b> 6 to 8 Years<br/><br/><b>Location : </b> Bangalore / Mumbai (Hybrid)<br/><br/><b>Job Summary : </b><br/><br/>We are looking for an experienced Associate Architect Machine Learning to join our team, focused on building Agentic AI workflows, fine-tuning Large Language Models (LLMs), performing prompt engineering, and applying related generative AI techniques.<br/><br/>The ideal candidate will have expertise in cutting-edge AI technologies and the ability to design, develop, and deploy AI solutions that can autonomously perform tasks with minimal human intervention.<br/><br/><b>Roles and Responsibilities : </b><br/><br/>- Agentic AI Development : Design, develop, and optimize domain adaptive agentic AI systems that helps in automating business processes.<br/><br/>- LLM Fine-Tuning : Work with large-scale pre-trained models (like Llama, Mistral etc.) to fine-tune with techniques like PEFT, SFT and adapt them for specific applications and domains.
Evaluate and Optimize for performance, accuracy, and efficiency.<br/><br/>- Prompt Engineering : Design prompts with techniques like Chain of Thought, Few Shot to enhance model responses, ensuring that model outputs are aligned with use case requirements.<br/><br/>- AI Workflow Automation : Build end-to-end workflows for AI solutions, from data collection and preprocessing to training, deployment, and continuous improvement in production environments.<br/><br/>- Collaboration with Cross-functional Teams : Work closely with data scientists, software engineers, and product managers to define AI product requirements and deliver innovative solutions.<br/><br/>- Research & Development : Stay current with the latest research and developments in generative AI, deep learning, NLP, reinforcement learning, and related fields to ensure that the organization stays at the forefront of technology.<br/><br/>- Scaling and Deployment : Deploy machine learning models at scale, optimizing for latency, throughput, and robustness in production environments.<br/><br/>- Documentation & Reporting : Maintain clear documentation of models, workflows, and experiments, and communicate results effectively to stakeholders.<br/><br/><b>Skill Set Required : </b><br/><br/><b>Experience : </b><br/><br/>- Minimum 5+ years of hands-on experience in machine learning and AI engineering.<br/><br/>- Proven track record in working with LLMs such as Llama, Mistral and models like GPT, BERT, T5, or similar.<br/><br/>- Expertise in designing, fine-tuning, and deploying generative AI models and building agentic workflows.<br/><br/>- Strong experience in prompt engineering to optimize AI models performance.<br/><br/><b>Technical Skills : </b><br/><br/>- Proficiency in Python, TensorFlow, PyTorch, or other ML frameworks.<br/><br/>- Proficiency in building agentic workflows with tools like Langgraph, CrewAI, Autogen, PhiData or similar.<br/><br/>- Familiarity with cloud platforms (AWS, GCP, Azure) for deployment and scaling of models.<br/><br/>- Experience with NLP tasks, such as text classification, text generation, summarization, and question answering.<br/><br/>- Knowledge of reinforcement learning, multi-agent systems, or other autonomous decision-making frameworks.<br/><br/>- Familiarity with SDLC life cycle , data processing tools (e.g., Pandas, NumPy, etc.) and version control (e.g., Git).<br/><br/><b>Soft Skills : </b><br/><br/>- Strong problem-solving and analytical skills.<br/><br/>- Excellent communication and teamwork abilities to collaborate with stakeholders.<br/><br/>- Ability to work independently and drive projects to completion with minimal supervision.<br/><br/><b>Preferred Skills & Qualifications : </b><br/><br/>- Experience in deploying AI models at scale in production environments.<br/><br/>- Expertise in large-scale data processing, optimization techniques, and model deployment</p><br/></p> (ref:hirist.tech)