Software Engineering Lead Analyst

Job Description

Required Skills: Foundations in Machine Learning and Deep Learning: Understanding algorithms, neural networks, supervised and unsupervised learning, and deep learning frameworks like TensorFlow, PyTorch, and Keras. Generative Models: Knowledge of generative models such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformers. Natural Language Processing (NLP): Knowledge in NLP techniques and libraries (e.g., spaCy, NLTK, Hugging Face Transformers) for text generation tasks. Model Deployment: Experience with deploying models using services like TensorFlow Serving, TorchServe, or cloud-based solutions (e.g., AWS SageMaker, Google AI Platform). Basic understanding of implementing Prompt Engineering, Finetuning and RAG. Strong foundation and practical experience in programming languages, especially Python, within the context of AI/ML workflows, crucial for transitioning from traditional software development processes to optimized and innovative solutions that enhance market agility. Containerization and Orchestration: Experience with Docker and Kubernetes / OpenShift for containerization and orchestration of applications. CI/CD Pipelines: Knowledge of continuous integration and continuous deployment tools and practices. Security Best Practices: understanding of security principles and best practices for protecting data and systems, including IAM, encryption and network Security. Cloud Services: Familiarity with cloud platforms like AWS / Google Cloud / Azure for deploying and managing applications and AI models. Required Experience & Education: A Bachelor's degree in Computer Science or a related field is required. A minimum of 5 years of experience in Software Development, including 3 years of professional experience in AI and Machine Learning engineering. At least 3 years of experience in Agile methodologies is required. Familiarity with an onshore/offshore operational model is essential. Demonstrated experience in the architecture, design and development of large-scale enterprise application solutions is required.