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
- Strong 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
