AI, Developer

• Design, develop, train, and optimize machine learning models for real applications or use cases. • Translate business and product requirements into scalable ML/AI solutions. • Implement feature engineering, model selection, tuning, and evaluation techniques. • Develop, and deploy ML models into production environments with high availability and performance. • Build and maintain ML pipelines (training, validation, deployment, monitoring). • Monitor model performance, data drift, and model decay; retrain models as needed. • Ensure models meet reliability, scalability, and security standards. • Work closely with Data Scientists, Product Managers, and Software Engineers. • Collaborate with data engineering teams to ensure high-quality, reliable data pipelines. • Participate in design and code reviews, ensuring engineering best practices. • Optimize models for latency, throughput, and cost. • Implement experimentation frameworks (A/B testing, offline evaluation). • Apply responsible AI principles, including fairness, explainability, and governance where required.

Requirements & Qualifications: • +4 years of hands-on experience in Machine Learning or applied AI roles. • Strong programming skills in Python (and/or Java, Scala). • Solid understanding of ML algorithms (supervised, unsupervised, deep learning). • Experience with frameworks such as TensorFlow, PyTorch, Scikit-learn. • Experience deploying models using Docker, Kubernetes, or cloud ML services. • Strong knowledge of data structures, algorithms, and software engineering principles. • Experience working in agile, cross-functional teams. • Experience with cloud platforms (AWS, Azure, or GCP) and managed ML services. • Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML). • Experience with big data technologies (Spark, Kafka, Databricks). • Background in NLP, Computer Vision, or Generative AI. • Strong problem-solving and analytical thinking • Production-first mindset • Data-driven decision making • High Collaboration and communication skills Tools & Technologies: • Dataiku • SQL server • Power bi, • Aws bedrock  Job Location: Client site

Master Works is seeking an AI, Developer to lead the development of intelligent solutions leveraging Artificial Intelligence technologies, with a focus on Generative AI and advanced analytics. The successful candidate will transform data into valuable business insights and develop AI-powered applications that drive smarter decision-making, improve operational efficiency, and support digital transformation initiatives. Key Responsibilities: • Design, develop, train, and optimize machine learning models for real applications or use cases. • Translate business and product requirements into scalable ML/AI solutions. • Implement feature engineering, model selection, tuning, and evaluation techniques. • Develop, and deploy ML models into production environments with high availability and performance. • Build and maintain ML pipelines (training, validation, deployment, monitoring). • Monitor model performance, data drift, and model decay; retrain models as needed. • Ensure models meet reliability, scalability, and security standards. • Work closely with Data Scientists, Product Managers, and Software Engineers. • Collaborate with data engineering teams to ensure high-quality, reliable data pipelines. • Participate in design and code reviews, ensuring engineering best practices. • Optimize models for latency, throughput, and cost. • Implement experimentation frameworks (A/B testing, offline evaluation). • Apply responsible AI principles, including fairness, explainability, and governance where required. Requirements & Qualifications: • +4 years of hands-on experience in Machine Learning or applied AI roles. • Strong programming skills in Python (and/or Java, Scala). • Solid understanding of ML algorithms (supervised, unsupervised, deep learning). • Experience with frameworks such as TensorFlow, PyTorch, Scikit-learn. • Experience deploying models using Docker, Kubernetes, or cloud ML services. • Strong knowledge of data structures, algorithms, and software engineering principles. • Experience working in agile, cross-functional teams. • Experience with cloud platforms (AWS, Azure, or GCP) and managed ML services. • Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML). • Experience with big data technologies (Spark, Kafka, Databricks). • Background in NLP, Computer Vision, or Generative AI. • Strong problem-solving and analytical thinking • Production-first mindset • Data-driven decision making • High Collaboration and communication skills Tools & Technologies: • Dataiku • SQL server • Power bi, • Aws bedrock  Job Location: Client site