Machine Learning Engineer
1 week ago
We are seeking a talented Machine Learning Engineer to drive the development of Agentic AI applications using Generative AI at Joist AI. In this role, you will focus on designing and deploying advanced machine learning models that power intelligent, autonomous agents to assist with specific workflows. You will work closely with our development team to ensure our AI systems are scalable, efficient, and continuously improving. Our right fit is someone who enjoys solving complex problems, thrives when learning new technologies, cares about scalability, interacts effectively in a team environment, and takes ownership and pride in their work.
What You'll Do:
- Design, develop, and deploy Generative AI models to support intelligent document automation and agent-based workflows.
- Work on agentic AI applications, enabling AI systems to take autonomous actions based on contextual understanding.
- Optimize and fine-tune large language models (LLMs).
- Build and maintain ML pipelines, ensuring high performance, scalability, and reliability.
- Collaborate with cross-functional teams to integrate AI solutions into our platform, making it seamless for users.
- Stay ahead of cutting-edge AI advancements, quickly prototyping and implementing novel solutions.
- Develop robust evaluation metrics to assess the effectiveness of generative models and agent-based AI solutions.
Background We're Looking For:
- Degree in Computer Science, Mathematics, AI, or a related technical field.
- 5+ years of experience in Machine Learning, with a recent focus on generative AI and autonomous agents.
- Strong knowledge of deep learning frameworks like PyTorch or TensorFlow.
- Experience working with LLMs (e.g., OpenAI, Claude, Mistral, Llama) and diffusion models.
- Proficiency in Python and experience with agentic libraries like Langraph, AutoGen, LlamaIndex, Crew AI, etc
- Familiarity with RAG, embeddings, and vector databases like FAISS, Pinecone, or Weaviate.
- Understanding of fine-tuning LLMs, prompt engineering, and reinforcement learning techniques.
- Experience in building AI-driven applications with APIs, cloud platforms, and microservices architectures.
- Ability to work independently and solve open-ended, ambiguous problems.
Experience We'd Be Particularly Excited About:
- Strong understanding of NLP, computer vision, or multi-modal AI applications.
- Experience with deploying AI models into production using AWS (Lambda, Step Functions, S3, RDS).
- Familiarity with MLOps practices, including model monitoring and continuous improvement.
- Open-source contributions, Kaggle competitions, or published research in GenAI.
What to Expect:
We conduct a rigorous interview process based on integrity, talent, and drive. The process typically takes two weeks:
1. Introductory Zoom Call (30 min) – Overview of Joist AI and discussion of your background.
2. Technical Interview (30 min) – Discuss your experience and approach to ML problem-solving.
3. Take-Home Project – Evaluate your ability to build and optimize ML models.
4. Project Review & Final Interview (60 min) – Deep dive into your project and final Q&A.
If you're excited about shaping the future of Agentic AI applications in a fast-paced startup environment, send your resume and a short statement on why you're interested in AI-driven automation to careers@joist.ai. We look forward to hearing from you
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