Senior Generative AI/LLM Engineer

We are seeking a highly skilled Senior Machine Learning Engineer with expertise in Generative AI and Large Language Models (LLMs) for our global clients and startups. This role involves designing, developing, and deploying scalable machine learning models and systems, focusing on innovative solutions that integrate cutting-edge LLM technologies. The ideal candidate will have a strong background in software engineering, data science, and AI, with a passion for creating efficient and reliable systems.

Key Responsibilities:

• Design and Implement Machine Learning Models: Develop and deploy applications and agents using state-of-the-art LLM technologies, tools and frameworks.
• Data Pipelines and Workflows: Design robust data pipelines for training and fine-tuning language models, and create intelligent automation workflows for software development and project management processes.
• Scalable Systems: Architect and implement scalable multi-agent systems using LLMs, ensuring high performance and reliability.
• Generative AI Applications: Scale Generative AI applications to handle large datasets and high user loads with optimized response times.
• Prompt Engineering: Develop and refine prompt strategies for effective LLM utilization.
• Pipeline Management: Set up and manage end-to-end pipelines involving vector databases, caching layers, and embedding systems.
• Collaboration and Innovation: Collaborate with cross-functional teams to drive innovation and contribute to the companys data strategy.
• Research and Development: Stay updated on the latest advancements in AI research and apply new findings to ongoing projects.

Required Skills:

• Technical Expertise:
  
• LLMs, RAG, Agentic Frameworks and fine tuning
• Strong background in Python, SQL, Linux/Unix shell scripting, NLP, PySpark, LLMs
• Proficiency in LLM solution patterns and tools (RAG, Graph, PEFT, Vector DB, Agentic workflows, LoRA, etc.).
• Experience with cloud platforms (AWS, Azure, GCP), machine learning services and DevOps tools.
• Familiarity with API frameworks (Fast API, Django) and web technologies (ReactJS, NodeJS, TypeScript).
• Machine Learning and AI:
  
• Expertise in Generative AI, including advanced RAG systems, prompt engineering and graph-based architectures.
• Strong understanding of LLM algorithms, RPA systems, and automation workflows.
• Experience with fine-tuning open-source models for production environments.
• Strong experience with LLM APIs (Open AI, Anthropic, AWS Bedrock), SDKs (Langchain, DSPy, LlamaIndex, CrewAI, AutoGen, etc)
• Pre-process data sets for LLM training, design benchmark tasks and perform experiments , build unit tests and implement model monitoring
• Software Engineering:
  
• Strong background in architecting reusable software components, frameworks, microservices, and APIs.
• Experience with CI/CD, AI/ML pipelines, and automation tools.
• Data Science:
  
• Proficiency in data science concepts, including statistical modeling and machine learning algorithms.
• Experience with data preprocessing, feature engineering, and model monitoring.

Preferred Qualifications:

• Education: Bachelors or Masters degree in Computer Science, Data Science, or a related field. A PhD in Computer Science is a plus.
• Experience: At least 5 years of experience in machine learning, data science, or a related field.
• Achievements: Successful track record in algorithms (ICPC / IOI), data science contests (Kaggle), or a HuggingFace leaderboard.
• Publications: Authoring a paper at a major Machine Learning conference.

Bonus Points:

• Innovation: Playing with new tools in the LLM stack and Agentic Frameworks.
• Code Portfolio: Showing a code portfolio demonstrating expertise in machine learning and software development.