AI/ML Engineer

ENVIRONMENT AN innovative Independent Asset Management Firm seeks to fill the critical role of an AI/ML Engineer who will design, develop, and deploy end-to-end AI/ML solutions and data pipelines that turn raw data into actionable insights, ensuring performance, scalability, and security. Working closely with cross-functional teams, you will help develop and deploy AI solutions, models and systems. Your role will involve researching, prototyping, and integrating cutting-edge AI technologies to solve complex business problems. Applicants will need 3+ years in AI/ML Engineering or Data Engineering roles, with end-to-end delivery with proficiency in Python, familiarity with Java or R. You will also be required to have a solid understanding of Machine Learning frameworks such as LangChain, PyTorch, Tensorflow or Hugging Face. DUTIES Transform requirements and build into AI solutions – Collaborate with Data Scientists, Software Engineers, and business stakeholders to define use cases and architecture for ML systems. Design and develop integrations with AI/ML technologies and data sources to leverage solutions for use cases. Work with AI/ML partners and internal teams to optimize and fine-tune AI models and use cases for performance, scalability, and accuracy. Deploy AI models and use cases into production environments, ensuring stability, reliability, and security. Monitor and evaluate the performance of deployed models and use cases, ensuring iterative improvements. Collaborate with Software Engineers to integrate AI/ML capabilities into existing or new software systems. Stay updated with the latest advancements in AI and Machine Learning research and apply relevant techniques to solve business challenges. Document and communicate AI solutions, methodologies, and best practices to technical and non-technical stakeholders. BUILD SCALABLE DATA PIPELINES Design, implement, and maintain data ingestion, preprocessing, and feature-engineering workflows using Big Data frameworks (Spark, Hadoop) and SQL expertia.ai. DEVELOP AND OPTIMIZE MODELS Research, prototype, and productionize ML algorithms with Python and frameworks such as PyTorch, TensorFlow, LangChain, or Hugging Face. Implement AI solutions using programming languages (such as Python) and Machine Learning frameworks (such as LangChain, PyTorch, Tensorflow or Hugging Face). Support Data Scientists and other stakeholders with collecting, processing, and analysing datasets to train and validate AI models. DEPLOY AND MONITOR IN THE CLOUD Containerize and orchestrate workloads (Docker, Kubernetes) and deploy models on Azure ensuring reliability and cost efficiency. ENSURE GOVERNANCE & SECURITY Implement data quality checks, versioning, and security best practices throughout ML pipelines in line with InfoSec standards. REQUIREMENTS 3+ Years in AI/ML Engineering or Data Engineering roles, with end-to-end delivery. Proficiency in Python; familiarity with Java or R. Understanding of Machine Learning frameworks such as LangChain, PyTorch, Tensorflow or Hugging Face. Experience with data preprocessing, feature engineering, and model evaluation techniques. Familiarity with Big Data processing frameworks (such as Hadoop or Spark) and SQL. Experience with Databricks and Mosaic. Hands-on with cloud ML services (e.g., SageMaker, Azure ML) and CI/CD pipelines for model deployment. ADVANTAGEOUS Knowledge of cloud platforms (such as AWS, Azure, or Google Cloud) and experience with deploying AI models on cloud infrastructure. ATTRIBUTES Ability to adapt to a fast-paced, dynamic work environment and quickly learn new technologies and techniques. Curiosity to learn about Artificial Intelligence, Machine Learning, Deep Learning concepts and data insights engines. Strong problem-solving and analytical skills, with the ability to understand complex business requirements and translate them into AI solutions. Able to explain complex technical concepts to both technical and non-technical audiences. #J-18808-Ljbffr