Job Description

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