JOB SUMMARY

ESSENTIAL FUNCTIONS

• Work closely with product managers to understand business requirements and translate them into technical solutions.
• Collaborate with data scientists, data engineers, data analysts, software engineers, IT specialists, and stakeholders to expand effective use of AI applications.
• Collaborate with cross-functional teams to design, develop, and maintain highly complex AI/ML systems.
• Develop and implement AI/ML interfaces, services, and analytic applications to support the company's initiatives and projects.
• Deploy machine learning models into production environments, ensuring scalability, reliability, and real-time performance. This may involve containerization, API development, and integration with existing systems.
• Optimize machine learning algorithms and infrastructure for performance, scalability, and cost-efficiency. This may involve parallelization, distributed computing, and resource management.
• Develop User Interfaces (UI) which support the business exploration and interaction with AI/ML models, scenarios, and planning.
• Work will business applications teams to code AI/ML intensive software and algorithms.
• Build services for driving intelligent decisions, interacting with machine learning models.
• Conduct research and stay updated on the latest advancements in AI/ML technology and tools.
• Analyze and optimize system performance to ensure efficient and effective use of resources.
• Deliver features to production while considering functional and non-functional requirements, including security, latency, disaster recovery, and performance.
• Take an active part in a Scrum team to deliver high quality software to the business.

SUPERVISORY RESPONSIBILITIES

This position may have direct reports depending on the project and organizational structure.

QUALIFICATIONS

• Bachelor’s degree in Computer Science, Computer Engineering, Information Technology or other relevant technical discipline
• 8 years of experience in developing business applications for Machine Learning and Data Science workloads.
• Strong programming skills in Python and Java; experience with Machine Learning libraries and frameworks.
• Experience with common data science tools such as Python, R, PyTorch, TensorFlow, Keras, NLTK, Spacy, or Neo4j, and a good understanding of modeling platforms such as SageMaker, Databricks, and Dataiku.
• Experience with data management technologies such as Databricks, Apache Spark, Hadoop, Kafka.
• Experience developing and deploying Machine Learning solutions on cloud platforms (e.g., AWS, Azure, or GCP). AWS Preferred.
• Experience containerizing analytical models using Docker and Kubernetes or other container orchestration platforms.
• Technical expertise across all deployment models on public cloud, private cloud, and on-premises infrastructure.
• Experience creating, documenting, and communicating software designs for complex products.
• Skilled with domain-driven, event-driven, and microservice architectures.
• Proficient in building, tracking, and communicating plans within agile processes.
• Capable of coaching/mentoring individuals and teams.