Job Title: Lead AI/ML Engineer
Location: St Petersburg, FL Headquarters; Denver, CO might be considered
Job Type: Permanent hire
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.
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), nonrelational (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.