Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
AI/ML Solutions Engineer
Miami Lakes, FL, USA
Live, first seen by us 39 days ago- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
- Not stated
- Employment
Full-time · Permanent — employment source
Employment type in the employer’s posting: Full Time - Permanent
From the employer’s posting
What you’ll work on
Full postingDesign and build generative AI applications for document analysis, chatbots and predictive models
Develop and maintain ML pipelines on AWS SageMaker or similar platforms
Build data pipelines and ETL processes that prepare data for AI/ML workflows
Evaluate, fine-tune and deploy large language models for financial services
Run model risk assessments and benchmarking, and set up monitoring for early risk detection
From the employer’s posting
Designs and implements generative AI applications for financial use cases, including document analysis, conversational interfaces, and predictive models
Develops and maintains machine learning pipelines using AWS SageMaker or similar cloud platforms
Designs and implements data pipelines to support AI/ML workflows on AWS
Evaluates, fine-tune, and deploys large language models for financial services applications
Performs comprehensive model risk assessments and develop mitigation strategies
What you’ll bring
All qualificationsCore experience
- 5+ years of experience
- Track record deploying generative AI solutions in production
- Strong Python and ML framework skills (PyTorch, TensorFlow, Hugging Face)
- Experience with AWS data services (S3, Glue, Redshift, Athena)
- Experience with SQL and NoSQL databases
Preferred experience
- Experience working with data scientists, product managers, and business units preferred
- Familiarity with AI orchestration and agent technologies preferred
- Experience developing model governance frameworks compatible with financial service regulations preferred
- Knowledge of prompt engineering and model fine-tuning techniques preferred
Qualification wording
5+ years of experience required
Proven track record of deploying generative AI solutions in production environments
Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, Hugging Face) required
Experience with AWS data services (S3, Glue, Redshift, Athena) required
Experience with SQL and NoSQL databases required
Experience working with data scientists, product managers, and business units preferred
Familiarity with AI orchestration and agent technologies preferred
Experience developing model governance frameworks compatible with financial service regulations preferred
Knowledge of prompt engineering and model fine-tuning techniques preferred
Education & alternatives
Education - Bachelor's Degree in Computer Science, Data Science, Mathematics, or related field or experience required Or Experience
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 26, 202639 days ago
- Recorded sightings
- 31
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 39
Similar jobs usually come down between day 6 and day 69.
From 4,331 similar postings that came down. Coming down is not always a hire.
Bankunited is hiring
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- Azure
- GCP
- NoSQL
- Redshift
- S3
- SageMaker
- Airflow
- Hugging Face
- PyTorch
- TensorFlow
Where the posting names them
Knowledge, Skills, and Abilities - Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, Hugging Face) required - Strong understanding of model risk management frameworks and methodologies required
- Experience with AWS data services (S3, Glue, Redshift, Athena) required - Experience with SQL and NoSQL databases required - Experience working with data scientists, product managers, and business units preferred
JOB SUMMARY: We are seeking an Artificial Intelligence/Machine Leaning (AI/ML) Solutions Engineer specialized in both AI & ML technologies and data engineering to join our data analytics team at BankUnited. In this role, you will design, develop, and deploy end-to-end AI & ML solutions that enhance our financial services, improve customer experiences, and optimize internal operations.This position offers an exciting opportunity to leverage your expertise in AI technologies and data engineering to transform our banking operations. You will be responsible for building comprehensive solutions from data pipeline development to AI/ML model deployment, addressing complex financial services challenges while working in a collaborative environment with cross-functional teams.As an ideal candidate, you will combine technical expertise in AI/ML with strong data engineering skills on AWS to build resilient, adaptable systems that can evolve with rapidly changing technologies. Success in this role requires practical implementation experience across the entire AI solution lifecycle - from data preparation and infrastructure design to model development and deployment - all within a regulated banking environment. ESSENTIAL DUTIES AND RESPONSIBILITIES:
- Designs and implements generative AI applications for financial use cases, including document analysis, conversational interfaces, and predictive models - Develops and maintains machine learning pipelines using AWS SageMaker or similar cloud platforms - Designs and implements data pipelines to support AI/ML workflows on AWS
- Develops and maintains machine learning pipelines using AWS SageMaker or similar cloud platforms - Designs and implements data pipelines to support AI/ML workflows on AWS - Develops ETL processes to prepare data for machine learning models
- Experience implementing model validation techniques and performance benchmarking required - Experience with AWS data services (S3, Glue, Redshift, Athena) required - Experience with SQL and NoSQL databases required
- Knowledge of best practices for mitigating AI-specific risks, including bias, drift, and adversarial vulnerabilities required - Familiarity with cloud-based ML platforms (AWS SageMaker, Azure ML, or GCP Vertex AI) required - Familiarity with data pipeline orchestration tools (e.g., AWS Step Functions, Airflow) required
- Familiarity with cloud-based ML platforms (AWS SageMaker, Azure ML, or GCP Vertex AI) required - Familiarity with data pipeline orchestration tools (e.g., AWS Step Functions, Airflow) required - Understanding of data modeling and database design principles required
Your next step
Complete your application on myjobs.adp.com. The employer’s form will show what is required.
Already applied? Track this application
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
JOB SUMMARY: We are seeking an Artificial Intelligence/Machine Leaning (AI/ML) Solutions Engineer specialized in both AI & ML technologies and data engineering to join our data analytics team at BankUnited. In this role, you will design, develop, and deploy end-to-end AI & ML solutions that enhance our financial services, improve customer experiences, and optimize internal operations.This position offers an exciting opportunity to leverage your expertise in AI technologies and data engineering to transform our banking operations. You will be responsible for building comprehensive solutions from data pipeline development to AI/ML model deployment, addressing complex financial services challenges while working in a collaborative environment with cross-functional teams.As an ideal candidate, you will combine technical expertise in AI/ML with strong data engineering skills on AWS to build resilient, adaptable systems that can evolve with rapidly changing technologies. Success in this role requires practical implementation experience across the entire AI solution lifecycle - from data preparation and infrastructure design to model development and deployment - all within a regulated banking environment.
ESSENTIAL DUTIES AND RESPONSIBILITIES:
- Designs and implements generative AI applications for financial use cases, including document analysis, conversational interfaces, and predictive models
- Develops and maintains machine learning pipelines using AWS SageMaker or similar cloud platforms
- Designs and implements data pipelines to support AI/ML workflows on AWS
- Develops ETL processes to prepare data for machine learning models
- Collaborates with stakeholders to identify opportunities for AI implementation and innovation
- Evaluates, fine-tune, and deploys large language models for financial services applications
- Performs comprehensive model risk assessments and develop mitigation strategies
- Designs and implements model benchmarking frameworks to evaluate performance, bias, and robustness
- Documents model limitations and establish monitoring systems for early risk detection
- Works with compliance teams to ensure AI systems meet regulatory requirements for model risk management
- Ensures AI systems comply with banking regulations and ethical standards
- Stays current with rapid advancements in AI technologies and methodologies.
- Adheres to and complies with applicable, federal and state laws, regulations and guidance, including those related to anti-money laundering (i.e. Bank Secrecy Act, US PATRIOT Act, etc.).
- Adheres to Bank policies and procedures and completes required training.
- Identifies and reports suspicious activity.
QUALIFICATIONS
Education
- Bachelor's Degree in Computer Science, Data Science, Mathematics, or related field or experience required Or
Experience
- 5+ years of experience required
- Proven track record of deploying generative AI solutions in production environments (eg, chatbots, content generation systems, or AI assistants) required
- Experience building and deploying machine learning models in production environments required
- Experience implementing model validation techniques and performance benchmarking required
- Experience with AWS data services (S3, Glue, Redshift, Athena) required
- Experience with SQL and NoSQL databases required
- Experience working with data scientists, product managers, and business units preferred
- Experience developing model governance frameworks compatible with financial service regulations preferred
- Experience with quantitative model risk assessment and establishment of risk thresholds preferred
- Proven track record working with various Machine Learning Models, implementing them for various business use cases preferred
- Expertise in designing controlled testing environments to benchmark model performance against established standards preferred
- Experience implementing RAG (Retrieval-Augmented Generation) systems and other LLM-enhancement architectures preferred
- Experience in a regulated industry, particularly financial services preferred
- Experience with vector databases and semantic search technologies preferred
- Experience developing scalable and maintainable AI infrastructures that accommodate rapid technological advancements
Licenses and Certifications
Knowledge, Skills, and Abilities
- Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, Hugging Face) required
- Strong understanding of model risk management frameworks and methodologies required
- Knowledge of best practices for mitigating AI-specific risks, including bias, drift, and adversarial vulnerabilities required
- Familiarity with cloud-based ML platforms (AWS SageMaker, Azure ML, or GCP Vertex AI) required
- Familiarity with data pipeline orchestration tools (e.g., AWS Step Functions, Airflow) required
- Understanding of data modeling and database design principles required
- Understanding of NLP concepts and experience working with language models required
- Knowledge of data security and privacy considerations, especially in financial contexts required
- Strong collaborative skills and experience working in cross-functional teams required
- Ability to communicate complex technical concepts to non-technical stakeholders required
- Proficiency in using Amazon Q Business for enterprise operations and solutions required
- Demonstrated passion for AI advancement, with a track record of self-directed learning, experimentation with emerging technologies, and willingness to pioneer innovative approaches preferred
- Familiarity with AI orchestration and agent technologies preferred
- Knowledge of prompt engineering and model fine-tuning techniques preferred
- Understanding of AI explainability and bias mitigation approaches preferred
- Forward-thinking approach to AI system design, with focus on adaptability and resilience preferred
- Deep understanding of cloud architecture principles to design modular, interchangeable systems preferred
- Demonstrated ability to anticipate technological changes and build solutions that can evolve preferred
Additional Information
Candidates residing in locations within BankUnited's footprint may be given preference.
Source details
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- Location & working pattern
Miami Lakes, FL, USA
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