- Design, develop, test, and deploy AI models and systems using various frameworks and tools.
- Monitor and evaluate the performance and accuracy of AI models and systems in production.
- Identify and troubleshoot issues related to data quality, model drift, scalability, and reliability.
- Optimize and automate the AI model lifecycle using MLOps best practices.
- Collaborate with data scientists, ML engineers, and business stakeholders to understand the requirements and objectives of AI projects.
- Research and implement new AI techniques and methodologies to improve the existing solutions and explore new opportunities.
- Research and Development: Stay abreast of the latest advancements in AI/GenIA, explore novel applications, and develop proof-of-concept projects.
- Model Selection and Fine-tuning: Select and fine-tune pretrained GenAI models (e.g., GPT4, LLaMa) for specific tasks, including text generation, image creation, code synthesis, etc.
- Data Exploration and Preparation: Prepare and analyze data sets for training and evaluation of GenAI models, ensuring data quality and addressing potential biases.
- Experimentation and Evaluation: Conduct experiments to assess the performance of GenAI models and compare different architectures and approaches.
- Application Integration: Develop and integrate GenAI models into existing or new applications, leveraging frameworks like LangChain for seamless orchestration.
- Collaborate with Cross-Functional Teams: Work closely with data scientists, software engineers, product managers, and designers to bring GenAI solutions to life.
- Contribute to Knowledge Sharing: Document your findings, share best practices, and contribute to the team's knowledge base.
What’s needed- Basic Qualifications
- Bachelor's degree or higher in Computer Science, Engineering, Mathematics, Statistics, or related field expertise.
- Strong experience in developing and deploying AI systems using Python, PyTorch, leveraging Databricks, Snowflake or similar frameworks and tools.
- Strong knowledge of machine learning, deep learning, natural language processing, computer vision, and other AI domains.
- Experience in prompt engineering, data preprocessing, model fine-tuning, and evaluation.
- Experience in MLOps, CI/CD, cloud computing, and containerization technologies.
- Excellent communication, collaboration, and problem-solving skills.
- Ability to work independently and in a team environment.
- Hands-on experience with popular GenAI LLM models (e.g., GPT-4o, Llama, Mixtral), SLM’s with Phi/Gamma/Triplex, and frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel, PyTorch, and long-term memory with Mem0 or similar.
- Degree in Computer Science, Artificial Intelligence, or a related field experience.
- 3+ years of experience in AI/ML, with a strong focus on Generative AI.
- Deep understanding of NLP, deep learning, and data analysis techniques.
- Experience with large language models (LLMs), text generation, and image gen.
- Strong programming skills in Python, along with experience in data manipulation libraries (e.g., Pandas, NumPy).
- Passion for innovation and a desire to explore the frontiers of AI.
What’s needed- Preferred Qualifications
- Experience with cloud platforms (Azure, GCP) and their AI/ML services.
- Familiarity with vector data stores (e.g., FAISS, Qdrant, Azure Search, Databricks