SSE- AI/ML

Job purpose:

Design, develop, and deploy end-to-end AI/ML systems, focusing on large language models (LLMs), prompt engineering, and scalable system architecture. Leverage technologies such as Java/Node.js/NET to build robust, high-performance solutions that integrate with enterprise systems.

Who You Are:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. PhD is a plus.
  
• 5+ years of experience in AI/ML development, with at least 2 years working on LLMs or NLP.
  
• Proven expertise in end-to-end system design and deployment of production-grade AI systems.
  
• Hands-on experience with Java/Node.js/.NET for backend development.
  
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Hugging Face Transformers).
  

Key Responsibilities:

1. Model Development & Training:

• Design, train, and fine-tune large language models (LLMs) for tasks such as natural language understanding, generation, and classification.
  
• Implement and optimize machine learning algorithms using frameworks like TensorFlow, PyTorch, or Hugging Face.
  

2. Prompt Engineering:

• Craft high-quality prompts to maximize LLM performance for specific use cases, including chatbots, text summarization, and question-answering systems.
  
• Experiment with prompt tuning and few-shot learning techniques to improve model accuracy and efficiency.
  

3. End-to-End System Design:

• Architect scalable, secure, and fault-tolerant AI/ML systems, integrating LLMs with backend services and APIs.
  
• Develop microservices-based architectures using Java/Node.js/.NET for seamless integration with enterprise applications.
  
• Design and implement data pipelines for preprocessing, feature engineering, and model inference.
  

4. Integration & Deployment:

• Deploy ML models and LLMs to production environments using containerization (Docker, Kubernetes) and cloud platforms (AWS/Azure/GCP).
  
• Build RESTful or GraphQL APIs to expose AI capabilities to front-end or third-party applications.
  

5. Performance Optimization:

• Optimize LLMs for latency, throughput, and resource efficiency using techniques like quantization, pruning, and model distillation.
  
• Monitor and improve system performance through logging, metrics, and A/B testing.
  

6. Collaboration & Leadership:

• Work closely with data scientists, software engineers, and product managers to align AI solutions with business objectives.
  
• Mentor junior engineers and contribute to best practices for AI/ML development.
  

What will excite us:

• Strong understanding of LLM architectures and prompt engineering techniques.
  
• Experience with backend development using Java/Node.js (Express)/.NET Core.
  
• Familiarity with cloud platforms (AWS, Azure, GCP) and DevOps tools (Docker, Kubernetes, CI/CD).
  
• Knowledge of database systems (SQL, NoSQL) and data pipeline tools (Apache Kafka, Airflow).
  
• Strong problem-solving and analytical skills.
  
• Excellent communication and teamwork abilities.
  
• Ability to work in a fast-paced, collaborative environment.
  

What will excite you:

• Lead AI innovation in a fast-growing, technology-driven organization.
  
• Work on cutting-edge AI solutions, including LLMs, autonomous AI agents, and Generative AI applications.
  
• Engage with top-tier enterprise clients and drive AI transformation at scale.