Lead AI/ML Engineer

Key Skills

Aartificial intelligence, Amazon RedShift, AWS, AWS Sagemaker, Azure, Data Analytics, Data science techniques, Git, Google Cloud Platform (GCP), Java Programming, Leadership Skill, Machine learning techniques, MLOps tools, Oracle, Postgres, Python Programming, SQL, Unix Operating system

Job Description

The Lead AI/ML Engineer will work closely with various business teams, Data Engineering, Data Science, Infrastructure teams to establish an AI/ML strategy and an AI/ML Platform which accelerates and standardizes AI/ML development for the enterprise. The Lead AI/ML engineer will be defining and refining the overall AI/ML Strategy for the firm working with the various product teams, business units, multiple data science teams, data and analytics teams and infrastructure teams. The Lead AI/ML engineer will establish the tools and solutions to enable AI/ML platforms and infrastructure, by partnering with various stakeholders across the organization. This will be a hybrid-based position in our St Petersburg, FL headquarters.

Essential Duties and Responsibilities: 

• Develops an enterprise AI/ML Strategy by working with various business units, data scientists, data and analytics teams, infrastructure and other stakeholders across the organization.
• Develops an AI/ML platform which will accelerate time to market in applying AI towards our business goals, democratize AI/ML, promote innovation, allow high skilled Data Scientists to focus on data science and help scale AI/ML with the right governance and security.
• Understands the overall data strategy, enterprise data stores, and establishes solutions to enable easy and consistent access to the data, for the scale of AI/ML development.
• Develops an AI/ML governance and be able to explain the framework.
• Develops a ML Ops end to end process which will enable model development, training, deployment, monitoring and inference.
• Develops solutions which will integrate AI/ML platforms and solutions with the various Analytical tools used to analyze and visualize data.
• Builds solutions on the cloud to leverage various cloud-based solutions to build resilient, scalable solutions.
• Develops solutions to seamlessly provision optimized infrastructure such as GPUs so that the Data Scientists can execute ML models against optimal infrastructure without infrastructure provisioning bottlenecks.
• Leads various POCs to establishing a cloud-based AI/ML Platform, Conversational/NLP based AI platforms and solutions and leads delivery of critical AI/ML initiatives across the firm.
• Delivers projects to successful completion as defined by predetermined project success criteria including those established by the business, ensuring that projects are delivered on time and within budget.
• Lead, coach, and develop team, while creating a vision for team and educating cross-functional teams on how to leverage data to identify opportunities to increase revenue and performance.
• Ability to work with multiple stakeholders and deliver solutions in an agile and nimble manner.
• Drives IT solutions to ensure they meet the business needs balanced with a pragmatic and integrated approach to the design of technical solutions.
• Focuses on workforce development and ensures that a strong team is built.
• Remains up to date on key technology, business, and industry trends.
• Performs other duties and responsibilities as assigned.

Qualifications

Experience and Skills:

• Minimum Bachelor’s degree in Computer Science, MIS, or related degree and a minimum of five (5) years of relevant development or engineering experience or combination of education, training, and experience.
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform.
• 3+ years of experience in developing AI/ML infrastructure and MLOps in the Cloud using solutions such as AWS SageMaker.
• Strong hands-on experience with AWS AI/ML services such as SageMaker, Comprehend, Rekognition, and others.
• Experience in Object Oriented Programming (Python or similar Java), SQL, Unix scripting or related programming languages and exposure to some of Python’s ML ecosystem (numpy, panda, sklearn, tensorflow, etc).
• Experience with Conversational AI products such as Kore.AI is preferred.
• Experience with deploying, optimizing and managing AI/ML models in production.
• Experience with CI/CD tools (e.g., Jenkins or equivalent) and version control (Git).
• Strong understanding of machine learning algorithms, model evaluation, and optimization techniques.
• Experience with data intensive analytical solutions leverages relational (Redshift, Oracle), non-relational (Postgres, Aurora, Graph databases) and search-based data platforms (SOLR, Open Search).
• Understanding of data engineering and ETL processes.
• Strong problem-solving skills, excellent written and verbal communication skills, and the ability to work in a fast-paced, dynamic environment.
• Financial Services experience is preferred.