We re seeking a talented Machine Learning Engineer to lead the development of Agentic AI applications that transform how organizations interact with intelligent automation You ll be at the forefront of building AI systems that don t just respond they think plan and act autonomously to solve complex workflows As one of our foundational AI team members you ll design and deploy cutting-edge Generative AI models that power intelligent document automation and sophisticated agent-based workflows This isn t just about implementing existing models you ll be pushing the boundaries of what s possible with autonomous AI agents creating systems that understand context make decisions and execute actions with minimal human intervention What You ll Do AI Model Development Deployment Build sophisticated agentic AI applications that enable autonomous decision-making and action execution Optimize and fine-tune large language models LLMs for specific use cases and performance requirements Develop novel approaches to agent reasoning planning and tool usage Production ML Systems Build and maintain robust ML pipelines ensuring high performance scalability and reliability in production Implement comprehensive evaluation frameworks to assess the effectiveness of generative models and agent-based solutions Design monitoring and feedback systems that enable continuous model improvement Optimize inference performance and cost efficiency at scale Innovation Research Stay ahead of cutting-edge AI advancements rapidly prototyping and implementing novel solutions Experiment with emerging agentic frameworks and contribute to the evolution of autonomous AI systems Collaborate with the research community through open-source contributions and knowledge sharing Drive technical innovation that gives Joist AI competitive advantages Cross-Functional Collaboration Partner with Product and Engineering teams to integrate AI solutions seamlessly into our platform Work with Product Marketing to translate technical capabilities into user-facing value propositions Collaborate with Customer Success to understand real-world usage patterns and optimization opportunities Mentor other engineers and contribute to building our AI engineering culture What You Bring Core Qualifications Degree in Computer Science Mathematics AI or related technical field 5 years of Machine Learning experience with recent focus on generative AI and autonomous agents Strong expertise in deep learning frameworks PyTorch or TensorFlow Hands-on experience with LLMs OpenAI Claude Mistral Llama and diffusion models Proficiency in Python and experience with agentic libraries Langraph LlamaIndex Crew AI etc Technical Expertise Deep understanding of RAG embeddings and vector databases FAISS Pinecone Weaviate Experience with fine-tuning LLMs prompt engineering and reinforcement learning techniques Proven track record building AI-driven applications with APIs cloud platforms and microservices Solid problem-solving skills with ability to tackle open-ended ambiguous challenges independently Mindset Approach Passion for solving complex problems and learning cutting-edge technologies Strong sense of ownership and pride in delivering high-quality solutions Excellent collaboration skills and thrives in team environments Care deeply about scalability reliability and production-ready systems Experience We d Be Particularly Excited About Deep expertise in NLP computer vision or multi-modal AI applications Production experience deploying AI models on AWS Lambda Step Functions S3 RDS Strong MLOps practices including model monitoring A B testing and continuous improvement Open-source contributions Kaggle competitions or published research in GenAI Experience with agent frameworks and tool-calling mechanisms Background in distributed systems and high-performance computing What We Offer Competitive salary Flexible PTO and remote work options Access to latest AI tools compute resources and research papers Opportunity to shape the future of autonomous AI applications Collaborative innovation-driven culture with direct access to leadership Conference speaking opportunities and support for open-source contributions Our Interview Process We conduct a thorough but respectful interview process designed to assess both technical skills and cultural fit Introductory Call 30 min - Learn about Joist AI s mission and discuss your background and interests Technical Deep Dive 45 min - Explore your experience with ML systems agentic AI and problem-solving approach Take-Home Project - Design and implement a solution that demonstrates your ML engineering skills Project Review Team Fit 60 min - Present your solution discuss technical decisions and meet potential teammates Typical timeline 2 weeks from application to offer Ready to Apply If you re excited about pioneering the next generation of Agentic AI applications and want to build autonomous systems that genuinely transform how work gets done we d love to hear from you Send your resume along with A brief note about why you re passionate about AI-driven automation Links to relevant projects papers or open-source contributions if applicable What excites you most about building agentic AI systems

📌 Machine Learning Engineer (India)
🏢 Joist AI
📍 India