(Senior) Machine Learning Engineer
2 days ago
Location : Mumbai / Bangalore / Trivandrum (hybrid)
We are looking for experienced Machine Learning Engineers 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. 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.
Agentic AI Development: Design, develop, and optimize domain adaptive agentic AI systems that helps in automating business processes
LLM Fine-Tuning: Work with large-scale pre-trained models (like Llama, Mistral etc.) Evaluate and Optimize for performance, accuracy, and efficiency.
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.
Collaboration with Cross-functional Teams: Work closely with data scientists, software engineers, and product managers to define AI product requirements and deliver innovative solutions.
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.
Scaling and Deployment: Deploy machine learning models at scale, optimizing for latency, throughput, and robustness in production environments.
Experience:
~3+ years of hands-on experience in machine learning and AI engineering.
~ Expertise in designing, fine-tuning, and deploying generative AI models and building agentic workflows.
~ Strong experience in prompt engineering to optimize AI models performance.
Proficiency in Python, TensorFlow, PyTorch, or other ML frameworks.
Proficiency in building agentic workflows with tools like Langgraph, CrewAI, Autogen, PhiData or similar.
Familiarity with cloud platforms (AWS, GCP, Azure) for deployment and scaling of models.
Experience with NLP tasks, such as text classification, text generation, summarization, and question answering.
Familiarity with SDLC life cycle , data processing tools (e.g., Ability to work independently and drive projects to completion with minimal supervision.
Experience in deploying AI models at scale in production environments.
Expertise in large-scale data processing, optimization techniques, and model deployment.
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