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About Pibit.ai
Generative AI
smarter, faster decisions
underwriting processes, reducing risk, and improving premiums. As we expand, we're
Machine Learning Engineer - 2
generate value for our customers.
Position Overview
As a MLE-2, you will design, implement, and optimize AI solutions while ensuring
model success. You will lead the ML lifecycle from development to deployment,
collaborate with cross-functional teams, and enhance AI capabilities to drive
innovation and impact.
Key Responsibilities:
- Design and implement AI product features.
- Maintain and optimize existing AI systems.
- Train, evaluate, deploy, and monitor ML models.
- Design ML pipelines for experiment, model, and feature management.
- Implement A/B testing and scalable model inferencing APIs.
- Optimize GPU architectures, parallel training, and fine-tune models for improved performance.
- Deploy LLM solutions tailored to specific use cases.
- Ensure DevOps and LLMOps best practices using Kubernetes, Docker, and orchestration frameworks.
Technical Requirements:
- LLM & ML: Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama
- LLMOps: MLFlow, Langchain, Langgraph, LangFlow, Langfuse, LlamaIndex, SageMaker, AWS Bedrock, Azure AI
- Databases: MongoDB, PostgreSQL, Pinecone, ChromDB
- Cloud: AWS, Azure
- DevOps: Kubernetes, Docker
- Languages: Python, SQL, JavaScript
- Certifications (Bonus): AWS Professional Solution Architect, AWS Machine Learning Specialty, Azure Solutions Architect Expert
What You'll Do:
- Collaborate with cross-functional teams to design and build scalable ML solutions.
- Implement state-of-the-art ML techniques, including NLP , Generative AI, RAG, and Transformer architectures.
- Deploy and monitor ML models for high performance and reliability.
- Innovate through research, staying ahead of industry trends.
- Build scalable data pipelines following best practices.
- Present key insights and drive decision-making.
What You Need to Succeed:
- Master's degree or equivalent experience in Machine Learning.
- 3+ years of industry experience in ML, software engineering, and data engineering.
- Proficiency in Python, PyTorch, TensorFlow, and Scikit-learn.
- Strong programming skills in Python and JavaScript.
- Hands-on experience with ML Ops practices.
- Ability to work with research and product teams.
- Excellent problem-solving skills and a track record of innovation.
- Passion for learning and applying the latest technological advancements.
Why Join Us
- Work directly with experienced founders.
- Be part of a high-energy team that works hard and celebrates success.
- Shape the future of AI-driven automation in the insurance industry.
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