Data Scientist (AI/ML)
Role summary
We are seeking a highly skilled and experienced Senior AI Developer to design, develop, and deploy cutting-edge AI solutions, focusing on agentic and conversational AI. The role requires a strong hands-on background with large language models (LLMs) and Python, along with experience deploying AI applications in cloud and on-premises environments. You will build intelligent agents and natural conversational interfaces to deliver impactful user experiences. Responsibilities include developing AI applications, implementing conversational agents, building agentic features, integrating and fine-tuning LLMs, writing Python code, deploying to cloud platforms (AWS, Azure, GCP), managing on-premises environments, and collaborating with cross-functional teams.
Job Summary (
Senior AI Developer)
: 100% Remote
We are seeking a highly skilled and experienced Senior AI Developer to play a pivotal role in designing, developing, and deploying cutting-edge AI solutions, with a particular focus on agentic and conversational AI. The ideal candidate will have a strong hands-on background in developing with large language models (LLMs), deep expertise in Python, and practical experience with deploying AI applications in both cloud and on-premises environments. You will be instrumental in building intelligent agents and natural conversational interfaces that deliver impactful user experiences.
Responsibilities:
- Develop AI Solutions:
Design, develop, and implement robust and scalable AI applications, with a strong emphasis on agentic workflows and conversational AI systems.
- Implement Conversational AI:
Build and optimize conversational AI agents, chatbots, and virtual assistants, focusing on natural language understanding (NLU), dialogue management, and response generation.
- Build Agentic AI Features:
Develop intelligent agent components capable of performing complex tasks, reasoning, and interacting autonomously with various systems.
- LLM Integration & Fine-tuning:
Work extensively with major Large Language Models (LLMs) (e.g., OpenAI models, Google Gemini, Anthropic Claude, open-source models), including API integration, prompt engineering, and fine-tuning for specific use cases.
- Python Development:
Write clean, efficient, and well-documented Python code for AI model development, data processing, API integrations, and application logic.
- Cloud Deployment:
Deploy and manage AI models and applications on major cloud platforms (AWS, Azure, GCP), leveraging their AI/ML services and infrastructure.
- On-Premises AI Environments:
Configure, optimize, and troubleshoot AI running environments on-premises, ensuring efficient resource utilization (GPUs, CPUs) and model serving.
- Code Review & Best Practices:
Participate in code reviews, contribute to architectural discussions, and promote best practices in software development and MLOps.
- Troubleshooting & Optimization:
Identify and resolve technical issues related to AI model performance, deployment, and integration. Optimize existing AI systems for efficiency and scalability.
- Collaboration:
Work closely with AI Architects, Data Scientists, Product Managers, and other engineering teams to translate requirements into technical specifications and deliver high-quality AI products.
- Stay Current:
Keep abreast of the latest advancements in AI, machine learning, LLMs, and relevant technologies.
Qualifications:
- Bachelor’s or master’s degree in computer science, Artificial Intelligence, Machine Learning, or a related technical field.
- Minimum of 5+ years of hands-on experience in software development, with at least 3 years specifically focused on AI/Machine Learning projects.
- Strong proficiency in Python
and experience with relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers).
- Demonstrable experience in developing and deploying agentic AI systems and/or conversational AI applications.
- Practical experience working with and integrating major Large Language Models (LLMs).
- Solid understanding of cloud computing concepts and hands-on experience with at least one major cloud provider (AWS, Azure, or GCP) for deploying AI/ML workloads.
- Experience with setting up and managing AI running environments, both in the cloud and on-premises (e.g., Docker, Kubernetes, GPU-enabled machines).
- Familiarity with API design and integration for AI services.
- Strong problem-solving skills, attention to detail, and a results-oriented approach.
- Excellent communication skills, both written and verbal, with the ability to articulate complex technical concepts.
Preferred Qualifications:
- Experience with specific agent frameworks (e.g., LangChain, LlamaIndex, AutoGen).
- Experience with conversational AI platforms/frameworks (e.g., Rasa, Dialogflow, Amazon Lex).
- Familiarity with MLOps principles and tools (e.g., MLflow, Kubeflow).
- Experience with database technologies (SQL/NoSQL) for managing AI-related data.
- Understanding of distributed systems and microservices architectures.
