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Manager Machine Learning Finance Jobs in Florida

Intraedge

Machine Learning Engineer

Sunrise, FL · On-site

Machine Learning Engineer - Generative Al Long term contract Sunrise, FL (Hybrid-3 days onsite ... Solid understanding of LLM memory architectures and state management. Proficiency in Python and ML ...

Amgen

Sr Machine Learning Engineer

Jacksonville, FL · On-site +1

$113K - $149K/yr

Ability to manage multiple priorities successfully. * Team-oriented, with a focus on achieving team ... financial plans with opportunities to save towards retirement or other goals, work/life balance ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

New

Elevance Health

AI Machine Learning Scientist

Tampa, FL · On-site +1

Non-Management Exempt Workshift: Job Family: IFT > Artificial Intelligence Please be advised that ... financial education resources, to name a few. Elevance Health operates in a Hybrid Workforce ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

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Manager Machine Learning Finance information

What does a Manager of Machine Learning in Finance do?

A Manager of Machine Learning in Finance oversees teams that develop and implement machine learning models to solve financial problems, such as risk assessment, fraud detection, and algorithmic trading. They coordinate with data scientists, engineers, and business stakeholders to ensure models meet regulatory standards and align with company goals. Additionally, they are responsible for project management, mentoring team members, and staying updated with advancements in both finance and artificial intelligence.

What are the key skills and qualifications needed to thrive as a Manager of Machine Learning in Finance, and why are they important?

To thrive as a Manager of Machine Learning in Finance, you need strong expertise in machine learning, statistics, and financial analysis, typically supported by a relevant advanced degree and experience in both data science and finance. Familiarity with programming languages like Python or R, cloud platforms, and machine learning frameworks such as TensorFlow or Scikit-learn is essential, along with knowledge of regulatory compliance systems. Exceptional leadership, strategic thinking, and communication skills set top candidates apart by enabling effective team management and cross-functional collaboration. These skills and qualities are crucial to drive innovative solutions, ensure regulatory adherence, and deliver business value in a complex financial environment.

What is the difference between Manager Machine Learning Finance vs Data Scientist Finance?

AspectManager Machine Learning FinanceData Scientist Finance
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or Finance; certifications in machine learning or data analysisBachelor's or Master's in Data Science, Statistics, or related fields; often includes certifications in data analysis or programming
Work EnvironmentLeads teams, manages projects, collaborates with stakeholders in financeAnalyzes data, develops models, supports decision-making in finance teams
Employer & Industry UsageFinancial institutions, hedge funds, investment firmsFinancial firms, banks, fintech companies

The Manager Machine Learning Finance oversees teams and projects applying machine learning to finance problems, focusing on leadership and strategy. In contrast, Data Scientists in finance primarily analyze data and develop models to support financial decisions. Both roles require strong technical skills, but the manager role emphasizes team management and project oversight.

How does a Manager of Machine Learning in Finance typically collaborate with cross-functional teams?

A Manager of Machine Learning in Finance often works closely with data scientists, software engineers, financial analysts, and business stakeholders. They are responsible for translating business problems into machine learning solutions and ensuring models meet both technical and regulatory requirements. Regular meetings and clear communication are essential, as the manager must align team efforts with organizational goals, facilitate knowledge sharing, and integrate model outputs into financial decision-making processes. Collaboration also involves coordinating with IT for data infrastructure and with compliance teams to uphold data privacy standards.
What are the most commonly searched types of Machine Learning Finance jobs in Florida? The most popular types of Machine Learning Finance jobs in Florida are:
What are popular job titles related to Manager Machine Learning Finance jobs in Florida? For Manager Machine Learning Finance jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Manager Machine Learning Finance jobs in Florida look for? The top searched job categories for Manager Machine Learning Finance jobs in Florida are:
What cities in Florida are hiring for Manager Machine Learning Finance jobs? Cities in Florida with the most Manager Machine Learning Finance job openings:
Manager Machine Learning Finance jobs near you
Infographic showing various Manager Machine Learning Finance job openings in Florida as of July 2026, with employment types broken down into 88% Full Time, 8% Part Time, 1% Temporary, and 3% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution.

Machine Learning Engineer

Tata Consultancy Service Limited

Sunrise, FL • On-site

$90K - $110K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted yesterday

Job description

Role - Machine Learning Engineer
Experience Required -8+ Years
We are seeking a Machine Learning Engineer to design, build, and deploy Generative AI solutions powered by Large Language Models (LLMs). In this role, you will work on end-to-end GenAI use cases, from model selection to production-ready systems. Key Responsibilities Develop and productionize GenAI applications using LLMs (open-source and closed-source). Design agentic workflows using LangChain and LangGraph.
Must Have Technical/Functional Skills:
We are seeking a Machine Learning Engineer to design, build, and deploy Generative AI solutions powered by Large Language Models (LLMs). In this role, you will work on end-to-end GenAI use cases, from model selection to production-ready systems. Key Responsibilities Develop and productionize GenAI applications using LLMs (open-source and closed-source). Design agentic workflows using LangChain and LangGraph.
• Implement short-term and long-term memory strategies for LLM-based systems.
• Optimize prompts, retrieval pipelines, and orchestration logic.
• Collaborate with product and platform teams to deliver scalable AI solutions.
Required Qualifications
• Strong experience with LLMs (e.g., OpenAI, Anthropic, Llama, Mistral)
• Hands-on experience with LangChain and/or LangGraph.
• Solid understanding of LLM memory architecture and state management.
• Proficiency in Python and ML engineering best practices.
Nice to Have
• Experience with GCP services (e.g., Vertex AI, BigQuery, GCS).
• Experience deploying ML/GenAI systems in production environments.
• data scientist
• Can do ML model
Roles & Responsibilities
• Design, develop, and deploy GenAI applications using LLMs.
• Build and implement agentic workflows using LangChain/LangGraph.
• Develop ML models and production-ready AI solutions.
• Implement and manage LLM memory and state management strategies.
• Optimize prompts, retrieval pipelines, and orchestration workflows.
• Collaborate with product and platform teams to deliver scalable AI solutions.
• Deploy, monitor, and maintain AI/ML systems in production environments.
• Evaluate and integrate open-source and proprietary LLMs.
Base Salary Range : $90,000 to $110,000 Per Annum
TCS Employee Benefits Summary:
Discretionary Annual Incentive.
Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
Family Support: Maternal & Parental Leaves.
Insurance Options : Auto & Home Insurance, Identity Theft Protection.
Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.
Time Off: Vacation, Time Off, Sick Leave & Holidays.
Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

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