Join Navatech Labs, where innovation meets excellence. Our forward-thinking team is dedicated toadvancing the construction industry through artificial intelligence. As a vital member of our AI team,you will be at the forefront of groundbreaking projects utilising GenAI, Natural LanguageProcessing (NLP), Large Language Model (LLM) training and tuning, MLOps, and Cloud
Key Responsibilities
Develop and implement innovative NLP algorithms and models to address complexbusiness challenges, Utilise large language models (LLMs) for natural language processingand generative AI tasks. Develop advanced generative AI solutions using open-sourceLLMs.
Participate in the training and fine-tuning of Large Language Models to ensure optimalperformance and accuracy. Assess machine learning model performance, iterate onimprovements, and apply best practices for model validation.
Collaborate with cross-functional teams to establish effective MLOps practices, ensuringseamless deployment, monitoring, and management of machine learning models. IntegrateAI solutions into existing platforms, working closely with various teams.
Leverage cloud platforms for scalable and efficient machine learning solutions, utilisingservices like AWS or Google Cloud.
Requirements
Professional Experience
Proven experience (2-3 years) in developing and deploying machine learning models, witha focus on NLP.
Experience in developing and deploying chatbot or conversational AI systems.
Technical Skills
Strong programming skills in languages such as Java and Python, and proficiency with MLframeworks (e.g., TensorFlow, PyTorch).
Experience in using LLMs for natural language processing or generative AI tasks.
Experience with MLOps tools and practices for model deployment, monitoring, andautomation.
Familiarity with cloud services and infrastructure for machine learning applications.
Strong understanding of AI, Generative AI patterns such as RAG and prompt engineeringtechniques.
Excellent problem-solving skills and a team-oriented mindset.
Strong communication skills to convey complex technical concepts to both technical andnon-technical stakeholders.