Senior Machine Learning Engineer
5 days ago
We are seeking experienced and creative professionals to join our team as Data Scientists. As a Data Scientist at our company, you will be responsible for designing, developing, and deploying novel solutions in the sales enterprise domain using cutting-edge AI technologies.
Key Responsibilities:- Design & Develop AI Solutions: Conceptualize, design, and implement robust and scalable applications leveraging Large Language Models (LLMs).
- Prompts Engineering: Develop, test, and refine complex prompts and prompt chains to steer model behavior, ensure accuracy, and optimize for performance and cost.
- Ai Orchestration: Build and deploy autonomous agents and multi-step workflows using frameworks like LangChain, LlamaIndex, or similar tools.
- Prototyping & Experimentation: Rapidly prototype new ideas, conduct experiments to evaluate different models and techniques, and present findings to technical and non-technical stakeholders.
- Evaluation & Monitoring: Establish robust metrics and evaluation frameworks to measure the quality and reliability of LLM outputs. Monitor and iterate on deployed applications to improve performance.
- Research & Innovation: Stay updated with the latest advancements in the field of Generative AI and proactively identify opportunities to apply new research to our products.
- 4+ years of experience in data science or applied machine learning, with a strong track record of delivering production-ready models.
- Practical experience with at least one major LLM application framework (LangChain, LlamaIndex, Semantic Kernel, LangGraph).
- Solid understanding of core machine learning concepts and the fundamentals of how LLMs work.
- Strong proficiency in Python and common data science libraries.
- Familiarity with cloud ecosystems, data pipelines, and distributed computing.
- Ability to independently own problem statements end-to-end while collaborating in a multi-disciplinary team.
- Excellent communication skills, with the ability to explain complex technical topics to product and business stakeholders.
- Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
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